{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "d4c9c6b6", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:09.587204Z", "iopub.status.busy": "2025-04-22T05:16:09.586867Z", "iopub.status.idle": "2025-04-22T05:16:23.191786Z", "shell.execute_reply": "2025-04-22T05:16:23.190704Z" }, "papermill": { "duration": 13.628776, "end_time": "2025-04-22T05:16:23.193750", "exception": false, "start_time": "2025-04-22T05:16:09.564974", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Standard libraries\n", "import os\n", "\n", "# Data manipulation\n", "import numpy as np\n", "import pandas as pd\n", "\n", "# Visualization\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "from IPython.display import display\n", "\n", "# Machine learning - scikit-learn\n", "from sklearn.model_selection import train_test_split, RandomizedSearchCV\n", "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.metrics import (\n", " classification_report, \n", " roc_auc_score,\n", " confusion_matrix, \n", " precision_recall_curve, \n", " auc,\n", " f1_score,\n", " precision_score, \n", " recall_score\n", ")\n", "\n", "# Machine learning - other frameworks\n", "import xgboost as xgb\n", "import lightgbm as lgb\n", "import shap\n", "\n", "# Imbalanced learning\n", "from imblearn.over_sampling import SMOTE\n", "from imblearn.pipeline import Pipeline as ImbPipeline" ] }, { "cell_type": "code", "execution_count": 2, "id": "51fcbe6e", "metadata": { "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", "execution": { "iopub.execute_input": "2025-04-22T05:16:23.234294Z", "iopub.status.busy": "2025-04-22T05:16:23.233618Z", "iopub.status.idle": "2025-04-22T05:16:23.245998Z", "shell.execute_reply": "2025-04-22T05:16:23.244775Z" }, "papermill": { "duration": 0.034418, "end_time": "2025-04-22T05:16:23.247701", "exception": false, "start_time": "2025-04-22T05:16:23.213283", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/kaggle/input/dspp1/product_info.csv\n", "/kaggle/input/dspp1/customer_product.csv\n", "/kaggle/input/dspp1/customer_info.csv\n", "/kaggle/input/dspp1/customer_cases.csv\n" ] } ], "source": [ "for dirname, _, filenames in os.walk('/kaggle/input'):\n", " for filename in filenames:\n", " print(os.path.join(dirname, filename))" ] }, { "cell_type": "markdown", "id": "5f701a0e", "metadata": { "papermill": { "duration": 0.018415, "end_time": "2025-04-22T05:16:23.285427", "exception": false, "start_time": "2025-04-22T05:16:23.267012", "status": "completed" }, "tags": [] }, "source": [ "## Load the Dataset" ] }, { "cell_type": "code", "execution_count": 3, "id": "7d9e375d", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:23.324816Z", "iopub.status.busy": "2025-04-22T05:16:23.324406Z", "iopub.status.idle": "2025-04-22T05:16:25.592907Z", "shell.execute_reply": "2025-04-22T05:16:25.592024Z" }, "papermill": { "duration": 2.290598, "end_time": "2025-04-22T05:16:25.594725", "exception": false, "start_time": "2025-04-22T05:16:23.304127", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "product_info = pd.read_csv(\"/kaggle/input/dspp1/product_info.csv\")\n", "customer_product = pd.read_csv(\"/kaggle/input/dspp1/customer_product.csv\")\n", "customer_info = pd.read_csv(\"/kaggle/input/dspp1/customer_info.csv\")\n", "customer_cases = pd.read_csv(\"/kaggle/input/dspp1/customer_cases.csv\")" ] }, { "cell_type": "markdown", "id": "3378d392", "metadata": { "papermill": { "duration": 0.018278, "end_time": "2025-04-22T05:16:25.631884", "exception": false, "start_time": "2025-04-22T05:16:25.613606", "status": "completed" }, "tags": [] }, "source": [ "## Exploratory Data Analysis" ] }, { "cell_type": "code", "execution_count": 4, "id": "6ec71cc7", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:25.669952Z", "iopub.status.busy": "2025-04-22T05:16:25.669600Z", "iopub.status.idle": "2025-04-22T05:16:25.674492Z", "shell.execute_reply": "2025-04-22T05:16:25.673630Z" }, "papermill": { "duration": 0.025755, "end_time": "2025-04-22T05:16:25.675997", "exception": false, "start_time": "2025-04-22T05:16:25.650242", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def style_df(df, caption=''):\n", " return df.style.set_caption(caption).set_table_styles([\n", " {'selector': 'th', 'props':[('background-color', '#f0f0f0'),\n", " ('color', 'black'),\n", " ('font-weight', 'bold')]},\n", " {'selector': 'tr:nth-of-type(odd)','props':[('background-color', '#f9f9f9')]},\n", " ])" ] }, { "cell_type": "code", "execution_count": 5, "id": "61789a51", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:25.714176Z", "iopub.status.busy": "2025-04-22T05:16:25.713824Z", "iopub.status.idle": "2025-04-22T05:16:25.794688Z", "shell.execute_reply": "2025-04-22T05:16:25.793641Z" }, "papermill": { "duration": 0.10197, "end_time": "2025-04-22T05:16:25.796477", "exception": false, "start_time": "2025-04-22T05:16:25.694507", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Customer Sign-up and Cancellation Dates
 Unnamed: 0customer_idproductsignup_date_timecancel_date_time
01C2448prd_12017-01-01 10:35:09nan
12C2449prd_12017-01-01 11:39:292021-09-05 10:00:02
23C2450prd_12017-01-01 11:42:002019-01-13 16:24:55
34C2451prd_22017-01-01 13:32:08nan
45C2452prd_12017-01-01 13:57:302021-06-28 18:06:01
\n" ], "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "style_df(customer_product.head(), 'Customer Sign-up and Cancellation Dates')" ] }, { "cell_type": "code", "execution_count": 6, "id": "b678989d", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:25.835574Z", "iopub.status.busy": "2025-04-22T05:16:25.835198Z", "iopub.status.idle": "2025-04-22T05:16:25.843351Z", "shell.execute_reply": "2025-04-22T05:16:25.842379Z" }, "papermill": { "duration": 0.029648, "end_time": "2025-04-22T05:16:25.844972", "exception": false, "start_time": "2025-04-22T05:16:25.815324", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Customer Demographics
 Unnamed: 0customer_idagegender
01C244876female
12C244961male
23C245058female
34C245162female
45C245271male
\n" ], "text/plain": [ "" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "style_df(customer_info.head(), 'Customer Demographics')" ] }, { "cell_type": "code", "execution_count": 7, "id": "c97aedd9", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:25.884536Z", "iopub.status.busy": "2025-04-22T05:16:25.884182Z", "iopub.status.idle": "2025-04-22T05:16:25.892651Z", "shell.execute_reply": "2025-04-22T05:16:25.891646Z" }, "papermill": { "duration": 0.03008, "end_time": "2025-04-22T05:16:25.894283", "exception": false, "start_time": "2025-04-22T05:16:25.864203", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Call Center Activity
 Unnamed: 0case_iddate_timecustomer_idchannelreason
01CC1012017-01-01 10:32:03C2448phonesignup
12CC1022017-01-01 11:35:47C2449phonesignup
23CC1032017-01-01 11:37:09C2450phonesignup
34CC1042017-01-01 13:28:14C2451phonesignup
45CC1052017-01-01 13:52:22C2452phonesignup
\n" ], "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "style_df(customer_cases.head(), 'Call Center Activity')" ] }, { "cell_type": "code", "execution_count": 8, "id": "5db7b6be", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:25.934188Z", "iopub.status.busy": "2025-04-22T05:16:25.933824Z", "iopub.status.idle": "2025-04-22T05:16:25.941577Z", "shell.execute_reply": "2025-04-22T05:16:25.940624Z" }, "papermill": { "duration": 0.029383, "end_time": "2025-04-22T05:16:25.943132", "exception": false, "start_time": "2025-04-22T05:16:25.913749", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Product Information
 product_idnamepricebilling_cycle
0prd_1annual_subscription120012
1prd_2monthly_subscription1251
\n" ], "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "style_df(product_info.head(), 'Product Information')" ] }, { "cell_type": "markdown", "id": "f852dde5", "metadata": { "papermill": { "duration": 0.018899, "end_time": "2025-04-22T05:16:25.981326", "exception": false, "start_time": "2025-04-22T05:16:25.962427", "status": "completed" }, "tags": [] }, "source": [ "Customer Product Table will be the centre of the star schema. customer_id will be the primary key linking to the customer_centre and customer_info. product_id will be the primary key for the product_info table" ] }, { "cell_type": "markdown", "id": "c188c23e", "metadata": { "papermill": { "duration": 0.019894, "end_time": "2025-04-22T05:16:26.020948", "exception": false, "start_time": "2025-04-22T05:16:26.001054", "status": "completed" }, "tags": [] }, "source": [ "### Data Preprocessing and Cleaning" ] }, { "cell_type": "code", "execution_count": 9, "id": "41f621b7", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:26.060755Z", "iopub.status.busy": "2025-04-22T05:16:26.060365Z", "iopub.status.idle": "2025-04-22T05:16:26.298849Z", "shell.execute_reply": "2025-04-22T05:16:26.297632Z" }, "papermill": { "duration": 0.260196, "end_time": "2025-04-22T05:16:26.300565", "exception": false, "start_time": "2025-04-22T05:16:26.040369", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "product_info missing values:\n", "product_id 0\n", "name 0\n", "price 0\n", "billing_cycle 0\n", "dtype: int64\n", "\n", "product_info data types:\n", "product_id object\n", "name object\n", "price int64\n", "billing_cycle int64\n", "dtype: object\n", "\n", "customer_product missing values:\n", "Unnamed: 0 0\n", "customer_id 0\n", "product 0\n", "signup_date_time 0\n", "cancel_date_time 396447\n", "dtype: int64\n", "\n", "customer_product data types:\n", "Unnamed: 0 int64\n", "customer_id object\n", "product object\n", "signup_date_time object\n", "cancel_date_time object\n", "dtype: object\n", "\n", "customer_info missing values:\n", "Unnamed: 0 0\n", "customer_id 0\n", "age 0\n", "gender 0\n", "dtype: int64\n", "\n", "customer_info data types:\n", "Unnamed: 0 int64\n", "customer_id object\n", "age int64\n", "gender object\n", "dtype: object\n", "\n", "customer_cases missing values:\n", "Unnamed: 0 0\n", "case_id 0\n", "date_time 0\n", "customer_id 0\n", "channel 0\n", "reason 0\n", "dtype: int64\n", "\n", "customer_cases data types:\n", "Unnamed: 0 int64\n", "case_id object\n", "date_time object\n", "customer_id object\n", "channel object\n", "reason object\n", "dtype: object\n" ] } ], "source": [ "for df_name, df in [(\"product_info\", product_info), \n", " (\"customer_product\", customer_product),\n", " (\"customer_info\", customer_info), \n", " (\"customer_cases\", customer_cases)]:\n", " print(f\"\\n{df_name} missing values:\")\n", " print(df.isnull().sum())\n", " \n", " print(f\"\\n{df_name} data types:\")\n", " print(df.dtypes)" ] }, { "cell_type": "code", "execution_count": 10, "id": "acc45e2f", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:26.341220Z", "iopub.status.busy": "2025-04-22T05:16:26.340853Z", "iopub.status.idle": "2025-04-22T05:16:26.443114Z", "shell.execute_reply": "2025-04-22T05:16:26.442122Z" }, "papermill": { "duration": 0.124196, "end_time": "2025-04-22T05:16:26.444631", "exception": false, "start_time": "2025-04-22T05:16:26.320435", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Unnamed: 0 0\n", "customer_id 0\n", "product 0\n", "signup_date_time 0\n", "cancel_date_time 396447\n", "dtype: int64" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "customer_product.isnull().sum()" ] }, { "cell_type": "markdown", "id": "90362af6", "metadata": { "papermill": { "duration": 0.019045, "end_time": "2025-04-22T05:16:26.483287", "exception": false, "start_time": "2025-04-22T05:16:26.464242", "status": "completed" }, "tags": [] }, "source": [ "This suggests that the missing values in cancel date_time are not actual missing values but rather customers who have not cancelled their subscription" ] }, { "cell_type": "code", "execution_count": 11, "id": "093fdcd0", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:26.523329Z", "iopub.status.busy": "2025-04-22T05:16:26.522970Z", "iopub.status.idle": "2025-04-22T05:16:26.857754Z", "shell.execute_reply": "2025-04-22T05:16:26.856494Z" }, "papermill": { "duration": 0.357222, "end_time": "2025-04-22T05:16:26.859703", "exception": false, "start_time": "2025-04-22T05:16:26.502481", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "customer_product['signup_date_time'] = pd.to_datetime(customer_product['signup_date_time'])\n", "customer_product['cancel_date_time'] = pd.to_datetime(customer_product['cancel_date_time'])\n", "customer_cases['date_time'] = pd.to_datetime(customer_cases['date_time'])" ] }, { "cell_type": "code", "execution_count": 12, "id": "99c42d60", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:26.899966Z", "iopub.status.busy": "2025-04-22T05:16:26.899634Z", "iopub.status.idle": "2025-04-22T05:16:26.928433Z", "shell.execute_reply": "2025-04-22T05:16:26.927574Z" }, "papermill": { "duration": 0.050872, "end_time": "2025-04-22T05:16:26.930281", "exception": false, "start_time": "2025-04-22T05:16:26.879409", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "today = pd.to_datetime('2022-01-01')\n", "customer_product['end_date'] = customer_product['cancel_date_time'].fillna(today)\n", "customer_product['tenure_days'] = (customer_product['end_date'] - customer_product['signup_date_time']).dt.days" ] }, { "cell_type": "markdown", "id": "a7642b20", "metadata": { "papermill": { "duration": 0.019411, "end_time": "2025-04-22T05:16:26.969301", "exception": false, "start_time": "2025-04-22T05:16:26.949890", "status": "completed" }, "tags": [] }, "source": [ "### Create a Joined Dataframe" ] }, { "cell_type": "code", "execution_count": 13, "id": "9efef458", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:27.009672Z", "iopub.status.busy": "2025-04-22T05:16:27.009256Z", "iopub.status.idle": "2025-04-22T05:16:27.441854Z", "shell.execute_reply": "2025-04-22T05:16:27.440628Z" }, "papermill": { "duration": 0.455052, "end_time": "2025-04-22T05:16:27.443863", "exception": false, "start_time": "2025-04-22T05:16:26.988811", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "joined_df = pd.merge(customer_product,customer_info, how='left', left_on='customer_id', right_on='customer_id')" ] }, { "cell_type": "code", "execution_count": 14, "id": "144c0619", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:27.484491Z", "iopub.status.busy": "2025-04-22T05:16:27.484136Z", "iopub.status.idle": "2025-04-22T05:16:27.676927Z", "shell.execute_reply": "2025-04-22T05:16:27.676057Z" }, "papermill": { "duration": 0.214986, "end_time": "2025-04-22T05:16:27.678721", "exception": false, "start_time": "2025-04-22T05:16:27.463735", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "joined_df = pd.merge(joined_df,product_info, how='left', left_on='product',right_on='product_id')" ] }, { "cell_type": "markdown", "id": "e62a0965", "metadata": { "papermill": { "duration": 0.018962, "end_time": "2025-04-22T05:16:27.762694", "exception": false, "start_time": "2025-04-22T05:16:27.743732", "status": "completed" }, "tags": [] }, "source": [ "Joining `customer_cases` with the rest of the DataFrame has a few complications. `customer_cases` exhibits one-to-many relationship problem, where a customer can have multiple support cases. Combining all the data into one table by directly joining results in duplicate customer records.\n", "\n", "To solve this, use aggregation, `groupby` and `.agg` operations transform this one-to-many relationship into a one-to-one relationship by summarizing all the `customer_cases` into one row" ] }, { "cell_type": "code", "execution_count": 15, "id": "f041d86e", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:27.802847Z", "iopub.status.busy": "2025-04-22T05:16:27.802438Z", "iopub.status.idle": "2025-04-22T05:16:28.221340Z", "shell.execute_reply": "2025-04-22T05:16:28.220411Z" }, "papermill": { "duration": 0.441067, "end_time": "2025-04-22T05:16:28.223189", "exception": false, "start_time": "2025-04-22T05:16:27.782122", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "case_summary = customer_cases.groupby('customer_id').agg({\n", "\t'case_id': 'count',\n", "\t'date_time':['min','max']\n", "})" ] }, { "cell_type": "code", "execution_count": 16, "id": "5a365f18", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:28.266320Z", "iopub.status.busy": "2025-04-22T05:16:28.265966Z", "iopub.status.idle": "2025-04-22T05:16:28.270312Z", "shell.execute_reply": "2025-04-22T05:16:28.269431Z" }, "papermill": { "duration": 0.027064, "end_time": "2025-04-22T05:16:28.271879", "exception": false, "start_time": "2025-04-22T05:16:28.244815", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "case_summary.columns = [\n", "\t'total_cases',\n", "\t'first_case_date',\n", "\t'last_case_date'\n", "]" ] }, { "cell_type": "code", "execution_count": 17, "id": "5a148755", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:28.312243Z", "iopub.status.busy": "2025-04-22T05:16:28.311874Z", "iopub.status.idle": "2025-04-22T05:16:28.325608Z", "shell.execute_reply": "2025-04-22T05:16:28.324496Z" }, "papermill": { "duration": 0.036035, "end_time": "2025-04-22T05:16:28.327505", "exception": false, "start_time": "2025-04-22T05:16:28.291470", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "case_summary['days_between_cases'] = (case_summary['last_case_date'] - case_summary['first_case_date']).dt.days" ] }, { "cell_type": "code", "execution_count": 18, "id": "f832ca2c", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:28.368183Z", "iopub.status.busy": "2025-04-22T05:16:28.367815Z", "iopub.status.idle": "2025-04-22T05:16:28.960532Z", "shell.execute_reply": "2025-04-22T05:16:28.959648Z" }, "papermill": { "duration": 0.615248, "end_time": "2025-04-22T05:16:28.962539", "exception": false, "start_time": "2025-04-22T05:16:28.347291", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Create separate columns for each reason and count the frequency of each reason\n", "\n", "reason_counts = customer_cases.groupby(['customer_id', 'reason']).size().unstack(fill_value=0)\n", "reason_counts.columns = [f\"reason{col}\" for col in reason_counts.columns]\n", "case_summary = case_summary.join(reason_counts)" ] }, { "cell_type": "code", "execution_count": 19, "id": "0e93ee66", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:29.003205Z", "iopub.status.busy": "2025-04-22T05:16:29.002844Z", "iopub.status.idle": "2025-04-22T05:16:29.454406Z", "shell.execute_reply": "2025-04-22T05:16:29.453397Z" }, "papermill": { "duration": 0.474152, "end_time": "2025-04-22T05:16:29.456406", "exception": false, "start_time": "2025-04-22T05:16:28.982254", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "churn_df = pd.merge(joined_df, case_summary, on='customer_id', how='left')" ] }, { "cell_type": "code", "execution_count": 20, "id": "71f82faa", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:29.496789Z", "iopub.status.busy": "2025-04-22T05:16:29.496436Z", "iopub.status.idle": "2025-04-22T05:16:29.508183Z", "shell.execute_reply": "2025-04-22T05:16:29.507299Z" }, "papermill": { "duration": 0.033829, "end_time": "2025-04-22T05:16:29.509970", "exception": false, "start_time": "2025-04-22T05:16:29.476141", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "churn_df['total_cases'] = churn_df['total_cases'].fillna(0)" ] }, { "cell_type": "code", "execution_count": 21, "id": "099a31fc", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:29.550185Z", "iopub.status.busy": "2025-04-22T05:16:29.549812Z", "iopub.status.idle": "2025-04-22T05:16:29.629196Z", "shell.execute_reply": "2025-04-22T05:16:29.628325Z" }, "papermill": { "duration": 0.101333, "end_time": "2025-04-22T05:16:29.631054", "exception": false, "start_time": "2025-04-22T05:16:29.529721", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "churn_df = churn_df.drop('Unnamed: 0_x', axis=1)\n", "churn_df = churn_df.drop('Unnamed: 0_y', axis=1)" ] }, { "cell_type": "code", "execution_count": 22, "id": "323ee71e", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:29.671950Z", "iopub.status.busy": "2025-04-22T05:16:29.671617Z", "iopub.status.idle": "2025-04-22T05:16:29.814326Z", "shell.execute_reply": "2025-04-22T05:16:29.813133Z" }, "papermill": { "duration": 0.165048, "end_time": "2025-04-22T05:16:29.816127", "exception": false, "start_time": "2025-04-22T05:16:29.651079", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "customer_id 0\n", "product 0\n", "signup_date_time 0\n", "cancel_date_time 396447\n", "end_date 0\n", "tenure_days 0\n", "age 0\n", "gender 0\n", "product_id 0\n", "name 0\n", "price 0\n", "billing_cycle 0\n", "total_cases 0\n", "first_case_date 250272\n", "last_case_date 250272\n", "days_between_cases 250272\n", "reasonsignup 250272\n", "reasonsupport 250272\n", "dtype: int64\n" ] } ], "source": [ "print(churn_df.isnull().sum())" ] }, { "cell_type": "markdown", "id": "801ef5c2", "metadata": { "papermill": { "duration": 0.020009, "end_time": "2025-04-22T05:16:29.856663", "exception": false, "start_time": "2025-04-22T05:16:29.836654", "status": "completed" }, "tags": [] }, "source": [ "## Clean Merged Dataset" ] }, { "cell_type": "code", "execution_count": 23, "id": "2271f271", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:29.898038Z", "iopub.status.busy": "2025-04-22T05:16:29.897679Z", "iopub.status.idle": "2025-04-22T05:16:29.923457Z", "shell.execute_reply": "2025-04-22T05:16:29.922606Z" }, "papermill": { "duration": 0.0485, "end_time": "2025-04-22T05:16:29.925253", "exception": false, "start_time": "2025-04-22T05:16:29.876753", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "churn_df['total_cases'] = churn_df['total_cases'].fillna(0)\n", "churn_df['first_case_date'] = churn_df['first_case_date'].fillna(pd.NaT)\n", "churn_df['last_case_date'] = churn_df['last_case_date'].fillna(pd.NaT)\n", "churn_df['days_between_cases'] = churn_df['days_between_cases'].fillna(0)\n", "churn_df['ever_contacted_support'] = churn_df['total_cases'].gt(0).astype(int)" ] }, { "cell_type": "code", "execution_count": 24, "id": "1a477c98", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:29.966158Z", "iopub.status.busy": "2025-04-22T05:16:29.965809Z", "iopub.status.idle": "2025-04-22T05:16:29.987271Z", "shell.execute_reply": "2025-04-22T05:16:29.986430Z" }, "papermill": { "duration": 0.0437, "end_time": "2025-04-22T05:16:29.989025", "exception": false, "start_time": "2025-04-22T05:16:29.945325", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "reason_columns = [col for col in churn_df.columns if col.startswith('reason')]\n", "churn_df[reason_columns] = churn_df[reason_columns].fillna(0)" ] }, { "cell_type": "code", "execution_count": 25, "id": "ee8d3da5", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:30.030066Z", "iopub.status.busy": "2025-04-22T05:16:30.029636Z", "iopub.status.idle": "2025-04-22T05:16:30.167148Z", "shell.execute_reply": "2025-04-22T05:16:30.165775Z" }, "papermill": { "duration": 0.160133, "end_time": "2025-04-22T05:16:30.169034", "exception": false, "start_time": "2025-04-22T05:16:30.008901", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "customer_id 0\n", "product 0\n", "signup_date_time 0\n", "cancel_date_time 396447\n", "end_date 0\n", "tenure_days 0\n", "age 0\n", "gender 0\n", "product_id 0\n", "name 0\n", "price 0\n", "billing_cycle 0\n", "total_cases 0\n", "first_case_date 250272\n", "last_case_date 250272\n", "days_between_cases 0\n", "reasonsignup 0\n", "reasonsupport 0\n", "ever_contacted_support 0\n", "dtype: int64\n" ] } ], "source": [ "print(churn_df.isnull().sum())" ] }, { "cell_type": "markdown", "id": "9f952a85", "metadata": { "papermill": { "duration": 0.020045, "end_time": "2025-04-22T05:16:30.210937", "exception": false, "start_time": "2025-04-22T05:16:30.190892", "status": "completed" }, "tags": [] }, "source": [ "## Defining Churn - Target Variable" ] }, { "cell_type": "markdown", "id": "b3dd69ce", "metadata": { "papermill": { "duration": 0.021165, "end_time": "2025-04-22T05:16:30.252311", "exception": false, "start_time": "2025-04-22T05:16:30.231146", "status": "completed" }, "tags": [] }, "source": [ "Earlier defined churn as has cancellation_date = Churned. This is good retrospectively, but it's not predictive. Using a time-window approach here (will churn in Next X Days). This is where the business value is. The purpose of churn prediction is preventing future churn, not explaining past churn" ] }, { "cell_type": "code", "execution_count": 26, "id": "2e416bed", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:30.293597Z", "iopub.status.busy": "2025-04-22T05:16:30.293211Z", "iopub.status.idle": "2025-04-22T05:16:30.309110Z", "shell.execute_reply": "2025-04-22T05:16:30.308250Z" }, "papermill": { "duration": 0.038614, "end_time": "2025-04-22T05:16:30.310907", "exception": false, "start_time": "2025-04-22T05:16:30.272293", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "cutoff_date = pd.to_datetime('2021-10-03')\n", "\n", "churn_df['will_churn_next_90d'] = (\n", " (churn_df['cancel_date_time'] > cutoff_date) & \n", " (churn_df['cancel_date_time'] <= cutoff_date + pd.Timedelta(days = 90))\n", ").astype(int)" ] }, { "cell_type": "markdown", "id": "56cce5c0", "metadata": { "papermill": { "duration": 0.019465, "end_time": "2025-04-22T05:16:30.350288", "exception": false, "start_time": "2025-04-22T05:16:30.330823", "status": "completed" }, "tags": [] }, "source": [ "## Feature Engineering" ] }, { "cell_type": "markdown", "id": "b08c4f84", "metadata": { "papermill": { "duration": 0.019282, "end_time": "2025-04-22T05:16:30.389345", "exception": false, "start_time": "2025-04-22T05:16:30.370063", "status": "completed" }, "tags": [] }, "source": [ "Tenure is one of the strongest predictors of churn in SaaS businesses. Subtracting the reference data (`today`) with the `signup_date_time`, gives tenure (`days_since_signup`)" ] }, { "cell_type": "code", "execution_count": 27, "id": "72199f39", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:30.429931Z", "iopub.status.busy": "2025-04-22T05:16:30.429585Z", "iopub.status.idle": "2025-04-22T05:16:30.450359Z", "shell.execute_reply": "2025-04-22T05:16:30.449521Z" }, "papermill": { "duration": 0.042998, "end_time": "2025-04-22T05:16:30.452115", "exception": false, "start_time": "2025-04-22T05:16:30.409117", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "churn_df['days_since_signup'] = (today - churn_df['signup_date_time']).dt.days " ] }, { "cell_type": "markdown", "id": "16239670", "metadata": { "papermill": { "duration": 0.023712, "end_time": "2025-04-22T05:16:30.496512", "exception": false, "start_time": "2025-04-22T05:16:30.472800", "status": "completed" }, "tags": [] }, "source": [ "Measures how long after signing up a customer first reached out to support (if they ever did). For the customers who did not contact support at all, fill the rows with -1 instead of 0. 0 would indicated the customer contacted support the exact same day they signed up. -1 or any negative value is impossible in real data, since a customer can't contact support before they signup" ] }, { "cell_type": "code", "execution_count": 28, "id": "30d2bdea", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:30.542994Z", "iopub.status.busy": "2025-04-22T05:16:30.542509Z", "iopub.status.idle": "2025-04-22T05:16:30.568194Z", "shell.execute_reply": "2025-04-22T05:16:30.567164Z" }, "papermill": { "duration": 0.048771, "end_time": "2025-04-22T05:16:30.570145", "exception": false, "start_time": "2025-04-22T05:16:30.521374", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "churn_df['age_group'] = pd.cut(churn_df['age'],\n", " bins = [0, 30, 45, 60, 75, 100],\n", " labels = ['<30', '30-45', '46-60','61-75','75+'])" ] }, { "cell_type": "code", "execution_count": 29, "id": "27b71be4", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:30.611631Z", "iopub.status.busy": "2025-04-22T05:16:30.611234Z", "iopub.status.idle": "2025-04-22T05:16:30.630018Z", "shell.execute_reply": "2025-04-22T05:16:30.628999Z" }, "papermill": { "duration": 0.041996, "end_time": "2025-04-22T05:16:30.632312", "exception": false, "start_time": "2025-04-22T05:16:30.590316", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "churn_df['tenure_group'] = pd.cut(churn_df['tenure_days'],\n", " bins = [0, 90, 180, 365, 730, float('inf')],\n", " labels = ['0-3mo', '3-6mo', '6-12mo','1-2yr', '2yr+'])" ] }, { "cell_type": "markdown", "id": "36229846", "metadata": { "papermill": { "duration": 0.019664, "end_time": "2025-04-22T05:16:30.674978", "exception": false, "start_time": "2025-04-22T05:16:30.655314", "status": "completed" }, "tags": [] }, "source": [ "Filter the dataset to keep only the customers who either churned after the cutoff date or who never churned at all. \n", "\n", "This approach ensures:\n", "\n", "- All customers in the dataset had enough time to show their behavior (signed up before cutoff)\n", "- The dataset avoids \"look-ahead bias\" by excluding customers who churned before the cutoff date\n", "- It creates a clear point-in-time snapshot where the modeling task becomes \"predict which active customers as of the cutoff date will eventually churn\"" ] }, { "cell_type": "code", "execution_count": 30, "id": "c9aa2697", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:30.716761Z", "iopub.status.busy": "2025-04-22T05:16:30.716351Z", "iopub.status.idle": "2025-04-22T05:16:30.887971Z", "shell.execute_reply": "2025-04-22T05:16:30.886730Z" }, "papermill": { "duration": 0.194911, "end_time": "2025-04-22T05:16:30.890441", "exception": false, "start_time": "2025-04-22T05:16:30.695530", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "modeling_df = churn_df[churn_df['signup_date_time'] < cutoff_date]\n", "\n", "modeling_df = modeling_df[\n", " (modeling_df['cancel_date_time'] > cutoff_date) | \n", " (modeling_df['cancel_date_time'].isna())\n", "]" ] }, { "cell_type": "code", "execution_count": 31, "id": "7d83aa30", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:30.940295Z", "iopub.status.busy": "2025-04-22T05:16:30.939830Z", "iopub.status.idle": "2025-04-22T05:16:30.979913Z", "shell.execute_reply": "2025-04-22T05:16:30.978624Z" }, "papermill": { "duration": 0.062854, "end_time": "2025-04-22T05:16:30.981638", "exception": false, "start_time": "2025-04-22T05:16:30.918784", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
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0C2448prd_12017-01-01 10:35:09NaT2022-01-01 00:00:00182576femaleprd_1annual_subscription...2017-01-01 10:32:032017-01-01 10:32:030.01.00.010182575+2yr+
1C2449prd_12017-01-01 11:39:292021-09-05 10:00:022021-09-05 10:00:02170761maleprd_1annual_subscription...2017-01-01 11:35:472017-01-01 11:35:470.01.00.010182561-752yr+
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5 rows × 23 columns

\n", "
" ], "text/plain": [ " customer_id product signup_date_time cancel_date_time \\\n", "0 C2448 prd_1 2017-01-01 10:35:09 NaT \n", "1 C2449 prd_1 2017-01-01 11:39:29 2021-09-05 10:00:02 \n", "2 C2450 prd_1 2017-01-01 11:42:00 2019-01-13 16:24:55 \n", "3 C2451 prd_2 2017-01-01 13:32:08 NaT \n", "4 C2452 prd_1 2017-01-01 13:57:30 2021-06-28 18:06:01 \n", "\n", " end_date tenure_days age gender product_id \\\n", "0 2022-01-01 00:00:00 1825 76 female prd_1 \n", "1 2021-09-05 10:00:02 1707 61 male prd_1 \n", "2 2019-01-13 16:24:55 742 58 female prd_1 \n", "3 2022-01-01 00:00:00 1825 62 female prd_2 \n", "4 2021-06-28 18:06:01 1639 71 male prd_1 \n", "\n", " name ... first_case_date last_case_date \\\n", "0 annual_subscription ... 2017-01-01 10:32:03 2017-01-01 10:32:03 \n", "1 annual_subscription ... 2017-01-01 11:35:47 2017-01-01 11:35:47 \n", "2 annual_subscription ... 2017-01-01 11:37:09 2017-01-01 11:37:09 \n", "3 monthly_subscription ... 2017-01-01 13:28:14 2017-03-31 12:06:58 \n", "4 annual_subscription ... 2017-01-01 13:52:22 2017-01-01 13:52:22 \n", "\n", " days_between_cases reasonsignup reasonsupport ever_contacted_support \\\n", "0 0.0 1.0 0.0 1 \n", "1 0.0 1.0 0.0 1 \n", "2 0.0 1.0 0.0 1 \n", "3 88.0 1.0 1.0 1 \n", "4 0.0 1.0 0.0 1 \n", "\n", " will_churn_next_90d days_since_signup age_group tenure_group \n", "0 0 1825 75+ 2yr+ \n", "1 0 1825 61-75 2yr+ \n", "2 0 1825 46-60 2yr+ \n", "3 0 1825 61-75 2yr+ \n", "4 0 1825 61-75 2yr+ \n", "\n", "[5 rows x 23 columns]" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "churn_df.head()" ] }, { "cell_type": "markdown", "id": "77a460e7", "metadata": { "papermill": { "duration": 0.020062, "end_time": "2025-04-22T05:16:31.023168", "exception": false, "start_time": "2025-04-22T05:16:31.003106", "status": "completed" }, "tags": [] }, "source": [ "Normalize billing calculations as monthly_spend. Currently, there are two main product types; a 125 monthly subscription (billing_cycles = 1) and a 1,200 annual subscription (billing_cycles = 12). Without normalization, the price difference makes it hard to compare these customers. The annual customer appears to spend much more, but their monthly commitment is similar. Monthly subscribers pay 25% more every month, which might influence their churn behavior" ] }, { "cell_type": "code", "execution_count": 32, "id": "6d4310f7", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:31.070506Z", "iopub.status.busy": "2025-04-22T05:16:31.069999Z", "iopub.status.idle": "2025-04-22T05:16:31.090136Z", "shell.execute_reply": "2025-04-22T05:16:31.088945Z" }, "papermill": { "duration": 0.048607, "end_time": "2025-04-22T05:16:31.092400", "exception": false, "start_time": "2025-04-22T05:16:31.043793", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "modeling_df['monthly_spend'] = modeling_df['price'] / modeling_df['billing_cycle']" ] }, { "cell_type": "code", "execution_count": 33, "id": "b88d1de4", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:31.146489Z", "iopub.status.busy": "2025-04-22T05:16:31.146115Z", "iopub.status.idle": "2025-04-22T05:16:31.170608Z", "shell.execute_reply": "2025-04-22T05:16:31.169530Z" }, "papermill": { "duration": 0.050037, "end_time": "2025-04-22T05:16:31.172952", "exception": false, "start_time": "2025-04-22T05:16:31.122915", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "modeling_df['tenure_at_cutoff'] = (cutoff_date - modeling_df['signup_date_time']).dt.days\n", "modeling_df['tenure_months'] = (modeling_df['tenure_at_cutoff'] / 30).round()" ] }, { "cell_type": "markdown", "id": "bedf55b5", "metadata": { "papermill": { "duration": 0.020052, "end_time": "2025-04-22T05:16:31.231028", "exception": false, "start_time": "2025-04-22T05:16:31.210976", "status": "completed" }, "tags": [] }, "source": [ "Measure how long after signing up a customer first reached out to support (if they ever did). For the customers who did not contact support at all, fill the rows with -1 instead of 0. 0 would indicated the customer contacted support the exact same day they signed up. -1 or any negative value is impossible in real data, since a customer can't contact support before they signup" ] }, { "cell_type": "code", "execution_count": 34, "id": "468091e6", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:31.273764Z", "iopub.status.busy": "2025-04-22T05:16:31.273372Z", "iopub.status.idle": "2025-04-22T05:16:31.317761Z", "shell.execute_reply": "2025-04-22T05:16:31.316655Z" }, "papermill": { "duration": 0.068404, "end_time": "2025-04-22T05:16:31.319824", "exception": false, "start_time": "2025-04-22T05:16:31.251420", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "mask = churn_df['ever_contacted_support'] == 1\n", "churn_df.loc[mask,'days_to_first_contact'] = (churn_df.loc[mask, 'first_case_date'] - churn_df.loc[mask, 'signup_date_time']).dt.days\n", "churn_df['days_to_first_contact'] = churn_df['days_to_first_contact'].fillna(-1)" ] }, { "cell_type": "markdown", "id": "5e074cc6", "metadata": { "papermill": { "duration": 0.021028, "end_time": "2025-04-22T05:16:31.361464", "exception": false, "start_time": "2025-04-22T05:16:31.340436", "status": "completed" }, "tags": [] }, "source": [ "Indicate whether a customer's *most recent support interaction occurred before* the defined `cutoff_date`" ] }, { "cell_type": "code", "execution_count": 35, "id": "8c937427", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:31.404799Z", "iopub.status.busy": "2025-04-22T05:16:31.404291Z", "iopub.status.idle": "2025-04-22T05:16:31.440419Z", "shell.execute_reply": "2025-04-22T05:16:31.439179Z" }, "papermill": { "duration": 0.060354, "end_time": "2025-04-22T05:16:31.442657", "exception": false, "start_time": "2025-04-22T05:16:31.382303", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "mask = modeling_df['ever_contacted_support'] == 1\n", "\n", "modeling_df.loc[mask, 'support_before_cutoff'] = (\n", " modeling_df.loc[mask, 'last_case_date'] < cutoff_date\n", ").astype(int)\n", "\n", "modeling_df['support_before_cutoff'] = modeling_df['support_before_cutoff'].fillna(0)" ] }, { "cell_type": "markdown", "id": "0ac01059", "metadata": { "papermill": { "duration": 0.019962, "end_time": "2025-04-22T05:16:31.491724", "exception": false, "start_time": "2025-04-22T05:16:31.471762", "status": "completed" }, "tags": [] }, "source": [ "Calculate how many days passed between the `cutoff_date` and the customer's last support contact, *but only if that last contact happened before the cutoff*." ] }, { "cell_type": "code", "execution_count": 36, "id": "d4c8c35b", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:31.547027Z", "iopub.status.busy": "2025-04-22T05:16:31.546502Z", "iopub.status.idle": "2025-04-22T05:16:31.585934Z", "shell.execute_reply": "2025-04-22T05:16:31.584845Z" }, "papermill": { "duration": 0.075544, "end_time": "2025-04-22T05:16:31.587727", "exception": false, "start_time": "2025-04-22T05:16:31.512183", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "mask = modeling_df['support_before_cutoff'] == 1\n", "modeling_df.loc[mask, 'days_since_last_contact'] = (\n", " cutoff_date - modeling_df.loc[mask, 'last_case_date']\n", ").dt.days\n", "\n", "modeling_df['days_since_last_contact'] = modeling_df['days_since_last_contact'].fillna(999)" ] }, { "cell_type": "markdown", "id": "97725c44", "metadata": { "papermill": { "duration": 0.020008, "end_time": "2025-04-22T05:16:31.628200", "exception": false, "start_time": "2025-04-22T05:16:31.608192", "status": "completed" }, "tags": [] }, "source": [ "Calculate the average frequency of support contacts per month over the customer's tenure " ] }, { "cell_type": "code", "execution_count": 37, "id": "2d424f46", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:31.670434Z", "iopub.status.busy": "2025-04-22T05:16:31.670073Z", "iopub.status.idle": "2025-04-22T05:16:31.701000Z", "shell.execute_reply": "2025-04-22T05:16:31.699901Z" }, "papermill": { "duration": 0.054271, "end_time": "2025-04-22T05:16:31.702897", "exception": false, "start_time": "2025-04-22T05:16:31.648626", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "mask = modeling_df['ever_contacted_support'] == 1\n", "\n", "modeling_df.loc[mask, 'monthly_contact_rate'] = (\n", " modeling_df.loc[mask, 'total_cases'] / (modeling_df.loc[mask, 'tenure_months'] + 1)\n", ")\n", "\n", "modeling_df['monthly_contact_rate'] = modeling_df['monthly_contact_rate'].fillna(0)" ] }, { "cell_type": "code", "execution_count": 38, "id": "4ce020eb", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:31.745467Z", "iopub.status.busy": "2025-04-22T05:16:31.744977Z", "iopub.status.idle": "2025-04-22T05:16:31.765263Z", "shell.execute_reply": "2025-04-22T05:16:31.764182Z" }, "papermill": { "duration": 0.043577, "end_time": "2025-04-22T05:16:31.767445", "exception": false, "start_time": "2025-04-22T05:16:31.723868", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "modeling_df['support_level'] = pd.cut(\n", " modeling_df['monthly_contact_rate'],\n", " bins = [-0.001, 0 , 0.2, 0.5, 1, float('inf')],\n", " labels = ['None', 'Low', 'Medium', 'High', 'Very High']\n", ")" ] }, { "cell_type": "code", "execution_count": 39, "id": "b00b588b", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:31.816669Z", "iopub.status.busy": "2025-04-22T05:16:31.816157Z", "iopub.status.idle": "2025-04-22T05:16:31.908010Z", "shell.execute_reply": "2025-04-22T05:16:31.906662Z" }, "papermill": { "duration": 0.115563, "end_time": "2025-04-22T05:16:31.910252", "exception": false, "start_time": "2025-04-22T05:16:31.794689", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Churn rate by age_group:\n", " mean count\n", "age_group \n", "75+ 4.382609 2875\n", "30-45 4.260450 24880\n", "46-60 4.008111 195279\n", "61-75 3.995778 163898\n", "<30 3.880597 1005\n", "\n", "Churn rate by tenure_group:\n", " mean count\n", "tenure_group \n", "0-3mo 75.802998 934\n", "3-6mo 4.752750 37452\n", "1-2yr 3.925560 119881\n", "6-12mo 3.703624 93260\n", "2yr+ 3.630965 136410\n", "\n", "Churn rate by support_level:\n", " mean count\n", "support_level \n", "Medium 4.955527 31480\n", "Very High 4.945055 546\n", "High 4.672024 5351\n", "Low 4.182353 162827\n", "None 3.704197 187733\n", "\n", "Churn rate by product:\n", " mean count\n", "product \n", "prd_2 5.389810 135348\n", "prd_1 3.288346 252589\n" ] } ], "source": [ "target = 'will_churn_next_90d'\n", "segments = ['age_group', 'tenure_group', 'support_level', 'product']\n", "\n", "for segment in segments:\n", " churn_by_segment = modeling_df.groupby(segment, observed=True)[target].agg(['mean', 'count'])\n", " churn_by_segment['mean'] *= 100\n", " print(f\"\\nChurn rate by {segment}:\")\n", " print(churn_by_segment.sort_values('mean', ascending=False))" ] }, { "cell_type": "markdown", "id": "e5c31ade", "metadata": { "papermill": { "duration": 0.020354, "end_time": "2025-04-22T05:16:31.959581", "exception": false, "start_time": "2025-04-22T05:16:31.939227", "status": "completed" }, "tags": [] }, "source": [ "Extremely high churn rate (76%) for customers with a tenure of 0-3 months. Might be dealing with 'onboarding cliff' in subscription businesses, could be a free trial effect, but the data does not indicate that the service offers a free trial, so I am making an assumption here. " ] }, { "cell_type": "code", "execution_count": 40, "id": "a03e5e1b", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:32.001989Z", "iopub.status.busy": "2025-04-22T05:16:32.001474Z", "iopub.status.idle": "2025-04-22T05:16:32.039164Z", "shell.execute_reply": "2025-04-22T05:16:32.037791Z" }, "papermill": { "duration": 0.061512, "end_time": "2025-04-22T05:16:32.041541", "exception": false, "start_time": "2025-04-22T05:16:31.980029", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " mean count\n", "tenure_weeks \n", "0 4.268293 2460\n", "1 4.101951 2511\n", "2 3.953749 2681\n", "3 3.834472 2634\n", "4 4.235727 2715\n", "5 3.463961 2858\n", "6 5.005325 2817\n", "7 3.766542 2947\n", "8 3.993344 3005\n", "9 4.386808 3123\n", "10 4.700991 3127\n", "11 3.773585 3180\n", "12 4.515522 3189\n", "product tenure_weeks\n", "prd_1 0 3.568465\n", " 1 2.510121\n", " 2 3.403933\n", " 3 3.448276\n", " 4 3.419453\n", " 5 2.620087\n", " 6 2.964570\n", " 7 2.746845\n", " 8 2.709848\n", " 9 2.927478\n", " 10 3.715992\n", " 11 2.754644\n", " 12 3.388747\n", "prd_2 0 4.940239\n", " 1 5.642633\n", " 2 4.488595\n", " 3 4.181687\n", " 4 5.003574\n", " 5 4.245283\n", " 6 6.973501\n", " 7 4.625000\n", " 8 5.294906\n", " 9 5.740741\n", " 10 5.617284\n", " 11 4.756022\n", " 12 5.600000\n", "Name: will_churn_next_90d, dtype: float64\n" ] } ], "source": [ "modeling_df['tenure_weeks'] = (modeling_df['tenure_at_cutoff'] / 7).astype(int)\n", "new_churn = modeling_df[modeling_df['tenure_at_cutoff'] < 90]\n", "weekly_churn = new_churn.groupby('tenure_weeks')['will_churn_next_90d'].agg(['mean','count'])\n", "weekly_churn['mean'] *= 100\n", "\n", "print(weekly_churn)\n", "\n", "new_product_churn = new_churn.groupby(['product', 'tenure_weeks'])['will_churn_next_90d'].mean() * 100\n", "\n", "print(new_product_churn)" ] }, { "cell_type": "code", "execution_count": 41, "id": "c35abcc1", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:32.090334Z", "iopub.status.busy": "2025-04-22T05:16:32.089852Z", "iopub.status.idle": "2025-04-22T05:16:32.107743Z", "shell.execute_reply": "2025-04-22T05:16:32.106648Z" }, "papermill": { "duration": 0.042046, "end_time": "2025-04-22T05:16:32.110310", "exception": false, "start_time": "2025-04-22T05:16:32.068264", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Count of customers in 0-3mo group: 934\n", "count 934.000000\n", "mean 23.361884\n", "std 23.019626\n", "min 0.000000\n", "25% 0.000000\n", "50% 18.000000\n", "75% 39.000000\n", "max 89.000000\n", "Name: tenure_at_cutoff, dtype: float64\n", "Churn rate in 0-3mo group: 75.80%\n", "product\n", "prd_1 71.111111\n", "prd_2 78.745645\n", "Name: will_churn_next_90d, dtype: float64\n" ] } ], "source": [ "tenure_check = modeling_df[modeling_df['tenure_group'] == '0-3mo']\n", "print(f\"Count of customers in 0-3mo group: {len(tenure_check)}\")\n", "\n", "print(tenure_check['tenure_at_cutoff'].describe())\n", "\n", "print(f\"Churn rate in 0-3mo group: {tenure_check['will_churn_next_90d'].mean()*100:.2f}%\")\n", "\n", "print(tenure_check.groupby('product')['will_churn_next_90d'].mean()*100)" ] }, { "cell_type": "markdown", "id": "85f87d22", "metadata": { "papermill": { "duration": 0.020297, "end_time": "2025-04-22T05:16:32.165658", "exception": false, "start_time": "2025-04-22T05:16:32.145361", "status": "completed" }, "tags": [] }, "source": [ "We have 934 customers who joined less than 3 months before the cutoff date. On average, these customers are only subscribed for 23 days. Half of them (median) have been customers for 18 days or less. 75% of the customers will cancel within the next 90 days. This is much higher than other tenure groups' 3-5% churn rate. There is also a difference in monthly subscribers (78.7%) who are more likely to churn compared to annual customers (71.1%)\n", "\n", "If we were to acquire 100 customers, ~75 would leave within the first 3 months. A large amount of leakage happening in the initial stages of the subscription signup\n", "\n", "The customer journey pattern seems to be Signup -> [Critical 3-month decision period] -> Stable Relationship" ] }, { "cell_type": "markdown", "id": "9585a6ba", "metadata": { "papermill": { "duration": 0.021607, "end_time": "2025-04-22T05:16:32.207791", "exception": false, "start_time": "2025-04-22T05:16:32.186184", "status": "completed" }, "tags": [] }, "source": [ "Given these dramatic differences, the best approach is segment-based modeling, particularly separating new customers from established ones " ] }, { "cell_type": "markdown", "id": "65ac88ac", "metadata": { "papermill": { "duration": 0.032732, "end_time": "2025-04-22T05:16:32.261979", "exception": false, "start_time": "2025-04-22T05:16:32.229247", "status": "completed" }, "tags": [] }, "source": [ "## Customer Segmentation" ] }, { "cell_type": "code", "execution_count": 42, "id": "640749c9", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:32.330485Z", "iopub.status.busy": "2025-04-22T05:16:32.329912Z", "iopub.status.idle": "2025-04-22T05:16:32.357340Z", "shell.execute_reply": "2025-04-22T05:16:32.356249Z" }, "papermill": { "duration": 0.064558, "end_time": "2025-04-22T05:16:32.359318", "exception": false, "start_time": "2025-04-22T05:16:32.294760", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "modeling_df['new_customer'] = modeling_df['tenure_at_cutoff'] < 90 # 0-3 months\n", "modeling_df.loc[modeling_df['new_customer'], 'signup_day_of_week'] = modeling_df.loc[modeling_df['new_customer'], 'signup_date_time'].dt.dayofweek\n", "modeling_df.loc[modeling_df['new_customer'], 'signup_month'] = modeling_df.loc[modeling_df['new_customer'], 'signup_date_time'].dt.month" ] }, { "cell_type": "code", "execution_count": 43, "id": "09f093ab", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:32.404238Z", "iopub.status.busy": "2025-04-22T05:16:32.403876Z", "iopub.status.idle": "2025-04-22T05:16:32.662377Z", "shell.execute_reply": "2025-04-22T05:16:32.661180Z" }, "papermill": { "duration": 0.282824, "end_time": "2025-04-22T05:16:32.664310", "exception": false, "start_time": "2025-04-22T05:16:32.381486", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "New customers: 37247 (9.6%)\n", "Established customers: 350690 (90.4%) \n" ] } ], "source": [ "new_customer_df = modeling_df[modeling_df['new_customer']].copy()\n", "established_customer_df = modeling_df[~modeling_df['new_customer']].copy()\n", "\n", "print(f\"New customers: {len(new_customer_df)} ({len(new_customer_df)/len(modeling_df):.1%})\")\n", "print(f\"Established customers: {len(established_customer_df)} ({len(established_customer_df)/len(modeling_df):.1%}) \")" ] }, { "cell_type": "markdown", "id": "1decdbf1", "metadata": { "papermill": { "duration": 0.020954, "end_time": "2025-04-22T05:16:32.707662", "exception": false, "start_time": "2025-04-22T05:16:32.686708", "status": "completed" }, "tags": [] }, "source": [ "Dealing with a significant class imbalance here - Will need feature engineering for each segment and then build separate models" ] }, { "cell_type": "markdown", "id": "4d4ad29b", "metadata": { "papermill": { "duration": 0.020081, "end_time": "2025-04-22T05:16:32.748392", "exception": false, "start_time": "2025-04-22T05:16:32.728311", "status": "completed" }, "tags": [] }, "source": [ "## New Customers" ] }, { "cell_type": "code", "execution_count": 44, "id": "c56c833b", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:32.790661Z", "iopub.status.busy": "2025-04-22T05:16:32.790207Z", "iopub.status.idle": "2025-04-22T05:16:32.794745Z", "shell.execute_reply": "2025-04-22T05:16:32.793619Z" }, "papermill": { "duration": 0.027614, "end_time": "2025-04-22T05:16:32.796482", "exception": false, "start_time": "2025-04-22T05:16:32.768868", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "new_features = [\n", " 'product',\n", " 'days_since_signup',\n", " 'ever_contacted_support',\n", " 'total_cases',\n", " 'age',\n", " 'gender',\n", " 'signup_month',\n", " 'signup_day_of_week'\n", "]" ] }, { "cell_type": "code", "execution_count": 45, "id": "6d8e3568", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:32.840459Z", "iopub.status.busy": "2025-04-22T05:16:32.840125Z", "iopub.status.idle": "2025-04-22T05:16:32.848166Z", "shell.execute_reply": "2025-04-22T05:16:32.847199Z" }, "papermill": { "duration": 0.032079, "end_time": "2025-04-22T05:16:32.849977", "exception": false, "start_time": "2025-04-22T05:16:32.817898", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "new_customer_df['signup_day_of_week'] = new_customer_df['signup_date_time'].dt.dayofweek\n", "new_customer_df['signup_month'] = new_customer_df['signup_date_time'].dt.month" ] }, { "cell_type": "code", "execution_count": 46, "id": "ccf31727", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:32.893489Z", "iopub.status.busy": "2025-04-22T05:16:32.893139Z", "iopub.status.idle": "2025-04-22T05:16:33.618870Z", "shell.execute_reply": "2025-04-22T05:16:33.617824Z" }, "papermill": { "duration": 0.749399, "end_time": "2025-04-22T05:16:33.620790", "exception": false, "start_time": "2025-04-22T05:16:32.871391", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "new_customer_df['days_to_first_contact'] = new_customer_df.apply(\n", " lambda x: (x['first_case_date'] - x['signup_date_time']).days\n", " if x['ever_contacted_support'] == 1 else -1, axis = 1\n", ")" ] }, { "cell_type": "markdown", "id": "b628066b", "metadata": { "papermill": { "duration": 0.020059, "end_time": "2025-04-22T05:16:33.661897", "exception": false, "start_time": "2025-04-22T05:16:33.641838", "status": "completed" }, "tags": [] }, "source": [ "### New Customer Baseline Model Building" ] }, { "cell_type": "code", "execution_count": 47, "id": "b516260c", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:33.703974Z", "iopub.status.busy": "2025-04-22T05:16:33.703625Z", "iopub.status.idle": "2025-04-22T05:16:35.715710Z", "shell.execute_reply": "2025-04-22T05:16:35.714723Z" }, "papermill": { "duration": 2.035172, "end_time": "2025-04-22T05:16:35.717383", "exception": false, "start_time": "2025-04-22T05:16:33.682211", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "New customer churn rate: 4.1587%\n", "Using class weights for new model: {0: 1, 1: 3}\n" ] }, { "data": { "text/html": [ "
RandomForestClassifier(class_weight={0: 1, 1: 3}, random_state=0)
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" ], "text/plain": [ "RandomForestClassifier(class_weight={0: 1, 1: 3}, random_state=0)" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X_new = new_customer_df[new_features]\n", "y_new = new_customer_df['will_churn_next_90d']\n", "\n", "X_new = pd.get_dummies(X_new, drop_first=True)\n", " \n", "X_train, X_test, y_train, y_test = train_test_split(\n", " X_new, y_new, test_size = 0.20, random_state = 0, stratify = y_new\n", ")\n", "new_churn_rate = y_new.mean()\n", "print(f\"New customer churn rate: {new_churn_rate: .4%}\")\n", "weights_new = {0:1, 1:3} # Non-churners get 3x the weight\n", "print(f\"Using class weights for new model: {weights_new}\")\n", "\n", "new_model = RandomForestClassifier(n_estimators = 100, class_weight = weights_new, random_state = 0)\n", "new_model.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "id": "feebaa90", "metadata": { "papermill": { "duration": 0.02026, "end_time": "2025-04-22T05:16:35.758742", "exception": false, "start_time": "2025-04-22T05:16:35.738482", "status": "completed" }, "tags": [] }, "source": [ "## Established Customers" ] }, { "cell_type": "code", "execution_count": 48, "id": "5e58e913", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:35.801335Z", "iopub.status.busy": "2025-04-22T05:16:35.800971Z", "iopub.status.idle": "2025-04-22T05:16:35.811519Z", "shell.execute_reply": "2025-04-22T05:16:35.810627Z" }, "papermill": { "duration": 0.033934, "end_time": "2025-04-22T05:16:35.813343", "exception": false, "start_time": "2025-04-22T05:16:35.779409", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "established_customer_df['billing_cycles_completed'] = (\n", " established_customer_df['tenure_days'] / (established_customer_df['billing_cycle'] * 30).astype(int) \n", ")\n", "\n", "established_customer_df['recent_support'] = (\n", " established_customer_df['days_since_last_contact'] < 30).astype(int)\n", "\n", "established_features = [\n", " 'tenure_group',\n", " 'product',\n", " 'support_level',\n", " 'days_since_last_contact',\n", " 'monthly_contact_rate',\n", " 'price',\n", " 'billing_cycle',\n", " 'age_group',\n", " 'gender',\n", " 'billing_cycles_completed',\n", " 'recent_support'\n", "]" ] }, { "cell_type": "markdown", "id": "0cd95df1", "metadata": { "papermill": { "duration": 0.020423, "end_time": "2025-04-22T05:16:35.854745", "exception": false, "start_time": "2025-04-22T05:16:35.834322", "status": "completed" }, "tags": [] }, "source": [ "### Established Customer Baseline Model Building" ] }, { "cell_type": "code", "execution_count": 49, "id": "2c547da6", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:16:35.901001Z", "iopub.status.busy": "2025-04-22T05:16:35.900637Z", "iopub.status.idle": "2025-04-22T05:17:12.925960Z", "shell.execute_reply": "2025-04-22T05:17:12.924627Z" }, "papermill": { "duration": 37.07012, "end_time": "2025-04-22T05:17:12.947383", "exception": false, "start_time": "2025-04-22T05:16:35.877263", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Established customer churn rate: 4.01%\n", "Using class weights for established model: {0: 1, 1: 5}\n" ] }, { "data": { "text/html": [ "
RandomForestClassifier(class_weight={0: 1, 1: 5}, random_state=0)
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" ], "text/plain": [ "RandomForestClassifier(class_weight={0: 1, 1: 5}, random_state=0)" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X_established = established_customer_df[established_features]\n", "y_established = established_customer_df['will_churn_next_90d']\n", "\n", "X_established = pd.get_dummies(X_established, drop_first = True, dummy_na = False)\n", "\n", "X_train_est, X_test_est, y_train_est, y_test_est = train_test_split(\n", " X_established, y_established,\n", " test_size = 0.20,\n", " random_state = 0,\n", " stratify = y_established\n", ")\n", "\n", "final_feature_names = X_established.columns.tolist() \n", "\n", "established_churn_rate = y_established.mean()\n", "print(f\"Established customer churn rate: {established_churn_rate: .2%}\")\n", "weight_est = {0:1,1:5}\n", "print(f\"Using class weights for established model: {weight_est}\")\n", "\n", "established_model = RandomForestClassifier(n_estimators=100,\n", " class_weight = weight_est,\n", " random_state = 0)\n", "\n", "established_model.fit(X_train_est, y_train_est)" ] }, { "cell_type": "markdown", "id": "a8ce8983", "metadata": { "papermill": { "duration": 0.020832, "end_time": "2025-04-22T05:17:12.989173", "exception": false, "start_time": "2025-04-22T05:17:12.968341", "status": "completed" }, "tags": [] }, "source": [ "## Baseline Model Evaluation" ] }, { "cell_type": "code", "execution_count": 50, "id": "ad412202", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:17:13.032361Z", "iopub.status.busy": "2025-04-22T05:17:13.031899Z", "iopub.status.idle": "2025-04-22T05:17:18.413803Z", "shell.execute_reply": "2025-04-22T05:17:18.412232Z" }, "papermill": { "duration": 5.405518, "end_time": "2025-04-22T05:17:18.415587", "exception": false, "start_time": "2025-04-22T05:17:13.010069", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Evaluating New Customer Model (Random Forest Baseline)...\n", "Evaluation Report for New Customer RF\n", " precision recall f1-score support\n", "\n", "No Churn (0) 0.96 0.97 0.97 7140\n", " Churn (1) 0.06 0.04 0.05 310\n", "\n", " accuracy 0.93 7450\n", " macro avg 0.51 0.51 0.51 7450\n", "weighted avg 0.92 0.93 0.93 7450\n", "\n", "ROC AUC Score: 0.5414\n", "Precision-Recall Curve AUC (PRC AUC): 0.0481\n", "\n", " Confusion Matrix:\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "Evaluating Established Customer Model (Random Forest Baseline) ...\n", "Evaluation Report for Established Customer RF\n", " precision recall f1-score support\n", "\n", "No Churn (0) 0.97 0.99 0.98 67328\n", " Churn (1) 0.59 0.32 0.42 2810\n", "\n", " accuracy 0.96 70138\n", " macro avg 0.78 0.66 0.70 70138\n", "weighted avg 0.96 0.96 0.96 70138\n", "\n", "ROC AUC Score: 0.7615\n", "Precision-Recall Curve AUC (PRC AUC): 0.4083\n", "\n", " Confusion Matrix:\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "def evaluate_model(model, X_test, y_test, model_name = \"Model\"):\n", " y_pred = model.predict(X_test)\n", " y_prob = model.predict_proba(X_test)[:,1]\n", "\n", " print(f'Evaluation Report for {model_name}')\n", " print(classification_report(y_test, y_pred, target_names = ['No Churn (0)', 'Churn (1)']))\n", "\n", " roc_auc = roc_auc_score(y_test, y_prob)\n", " print(f'ROC AUC Score: {roc_auc:.4f}')\n", "\n", " precision, recall, _ = precision_recall_curve(y_test, y_prob)\n", " prc_auc = auc(recall, precision)\n", " print(f'Precision-Recall Curve AUC (PRC AUC): {prc_auc:.4f}')\n", "\n", " cm = confusion_matrix(y_test, y_pred)\n", " print(\"\\n Confusion Matrix:\")\n", "\n", " plt.figure(figsize = (6,4))\n", " sns.heatmap(cm, annot = True, fmt='d', cmap='Blues',\n", " xticklabels = ['Predicted No Churn', 'Predicted Churn'],\n", " yticklabels = ['Actual No Churn', 'Actual Churn'])\n", " plt.title(f'Confusion Matrix - {model_name}')\n", " plt.ylabel('Actual Label')\n", " plt.xlabel('Predicted Label')\n", " plt.show()\n", "\n", " print(\"\"* (len(model_name) +24))\n", "\n", " return {\n", " 'roc_auc': roc_auc,\n", " 'prc_auc': prc_auc,\n", " 'f1_churn': f1_score(y_test, y_pred, pos_label=1),\n", " 'recall_churn': recall_score(y_test, y_pred, pos_label=1),\n", " 'precision_churn': precision_score(y_test, y_pred, pos_label=1)\n", " }\n", "\n", "print(\"Evaluating New Customer Model (Random Forest Baseline)...\")\n", "new_model_metrics = evaluate_model(new_model, X_test, y_test, 'New Customer RF')\n", "\n", "print(\"\\nEvaluating Established Customer Model (Random Forest Baseline) ...\")\n", "established_model_metrics = evaluate_model(established_model, X_test_est, y_test_est, \"Established Customer RF\")\n", "\n", "baseline_metrics = {\n", " 'New RF': new_model_metrics,\n", " 'Established RF': established_model_metrics\n", "}" ] }, { "cell_type": "markdown", "id": "007287ba", "metadata": { "papermill": { "duration": 0.022981, "end_time": "2025-04-22T05:17:18.462828", "exception": false, "start_time": "2025-04-22T05:17:18.439847", "status": "completed" }, "tags": [] }, "source": [ "New Customer Random Forest Baseline\n", "\n", "- `Precision: 0.06` - Extremely poor, when this model predicts a new customer will churn, it is right 6% of the time\n", "- `Recall: 0.04` - Extremely poor, model only identifies 4% of the new customers who actually churned, it missed 96% of them\n", "- `F1-score: 0.05` - Extremely poor, confirms the model is failing badly on the churn class\n", "\n", "Overall metrics\n", "\n", "- `Accuracy: 0.93` - Looks high but is very misleading: Since only ~4% of churn (310/7450), a model predicting ‘No Churn’ for everyone would get a ~96% accuracy, this model isn’t much better\n", "- `ROC AUC: 0.5414` - Very close to 0.5 (random chance) - indicates the model has almost no ability to distinguish between churning and non-churning new customers\n", "- `PRC AUC: 0.0481` - Extremely low. For an imbalanced dataset like this (~4% positive), a random model would have a PRC AUC of around 0.04, this model is barely above random guessing\n", "\n", "The baseline Random Forest for **new customers is performing terribly**. The class weights were not enough, It has no predictive power for identifying churn in this segment. Will need to try different features and algorithm. **Will need to put this segment on hold for now**\n", "\n", "-----------------------------------------------\n", "\n", "Established Customer Random Forest Baseline\n", "\n", "Performance on Churn (Class ‘1’)\n", "\n", "- `Precision: 0.59` - Decent. When this model predicts an established customer will churn, it’s correct 59% of the time - useable but still means 41% are false alarms\n", "- `Recall: 0.32` - Poor. The model only identifies 32% (less than a 3rd) of the established customer who churned. It misses the majority (68%)\n", "- `F1-score: 0.42` - Mediocre. Balanced score reflecting decent precision but poor recall\n", "\n", "Overall metrics:\n", "\n", "- `Accuracy: 0.96` - High, but again, influenced by the imbalance (~4% churn rate)\n", "- `ROC AUC: 0.7615` - Fair/Okay, significantly better than the random 0.5. Shows some ability to distinguish between classes\n", "- `PRC AUC: 0.4093`- Fair/Okay. Considerably better than random (~0.04) for this imbalance level. Indicates reasonable predictive signal\n", "\n", "The baseline Random Forest for **established customers shows potential but is flawed**. It is significantly better than the new customer model. Its main weakness is **low recall** - failing to identify most customers who will churn. The 5x weight class helped precision but wasn’t enough to catch more churners" ] }, { "cell_type": "markdown", "id": "c9304b38", "metadata": { "papermill": { "duration": 0.022608, "end_time": "2025-04-22T05:17:18.508446", "exception": false, "start_time": "2025-04-22T05:17:18.485838", "status": "completed" }, "tags": [] }, "source": [ "## Established Customer XGBoost Modeling and Tuning" ] }, { "cell_type": "code", "execution_count": 51, "id": "d8df5c5f", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:17:18.555797Z", "iopub.status.busy": "2025-04-22T05:17:18.555408Z", "iopub.status.idle": "2025-04-22T05:17:21.425280Z", "shell.execute_reply": "2025-04-22T05:17:21.423881Z" }, "papermill": { "duration": 2.895553, "end_time": "2025-04-22T05:17:21.426926", "exception": false, "start_time": "2025-04-22T05:17:18.531373", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Calculated scale_pos_weight for Established XGBoost: 23.96\n", "\n", "Training default XGBoost model for Established Customers...\n", "\n", "Evaluating Established Customer Model (XGBoost Default)...\n", "Evaluation Report for Established Customer XGB\n", " precision recall f1-score support\n", "\n", "No Churn (0) 0.98 0.86 0.92 67328\n", " Churn (1) 0.15 0.59 0.24 2810\n", "\n", " accuracy 0.85 70138\n", " macro avg 0.57 0.73 0.58 70138\n", "weighted avg 0.95 0.85 0.89 70138\n", "\n", "ROC AUC Score: 0.8201\n", "Precision-Recall Curve AUC (PRC AUC): 0.4760\n", "\n", " Confusion Matrix:\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "# XGBoost\n", "\n", "neg_count_est = (y_train_est == 0).sum()\n", "pos_count_est = (y_train_est == 1).sum()\n", "scale_pos_weight_est = neg_count_est / pos_count_est\n", "print(f'\\nCalculated scale_pos_weight for Established XGBoost: {scale_pos_weight_est:.2f}')\n", "\n", "xgb_model_est = xgb.XGBClassifier(\n", " objective = 'binary:logistic',\n", " eval_metric = 'logloss',\n", " use_label_encoder = False,\n", " scale_pos_weight = scale_pos_weight_est,\n", " random_state = 0\n", ")\n", "\n", "print('\\nTraining default XGBoost model for Established Customers...')\n", "xgb_model_est.fit(X_train_est, y_train_est)\n", "\n", "print('\\nEvaluating Established Customer Model (XGBoost Default)...')\n", "xgb_est_metrics = evaluate_model(xgb_model_est, X_test_est, y_test_est, 'Established Customer XGB')" ] }, { "cell_type": "markdown", "id": "26b91590", "metadata": { "papermill": { "duration": 0.023811, "end_time": "2025-04-22T05:17:21.474975", "exception": false, "start_time": "2025-04-22T05:17:21.451164", "status": "completed" }, "tags": [] }, "source": [ "Established Customer Model:\n", "\n", " The RF baseline missed too many churners (low recall).\n", " The default XGBoost found more churners (good recall) but was very inaccurate in its churn predictions (low precision).\n", " XGBoost shows more promise due to higher AUC scores, indicating better potential." ] }, { "cell_type": "markdown", "id": "4cb0d759", "metadata": { "papermill": { "duration": 0.023797, "end_time": "2025-04-22T05:17:21.522825", "exception": false, "start_time": "2025-04-22T05:17:21.499028", "status": "completed" }, "tags": [] }, "source": [] }, { "cell_type": "markdown", "id": "27c5a169", "metadata": { "papermill": { "duration": 0.023629, "end_time": "2025-04-22T05:17:21.570462", "exception": false, "start_time": "2025-04-22T05:17:21.546833", "status": "completed" }, "tags": [] }, "source": [ "### XGBoost Tuning" ] }, { "cell_type": "code", "execution_count": 52, "id": "f4e32f9e", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:17:21.620328Z", "iopub.status.busy": "2025-04-22T05:17:21.619920Z", "iopub.status.idle": "2025-04-22T05:30:44.245768Z", "shell.execute_reply": "2025-04-22T05:30:44.244220Z" }, "papermill": { "duration": 802.677282, "end_time": "2025-04-22T05:30:44.272091", "exception": false, "start_time": "2025-04-22T05:17:21.594809", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Starting Randomized Search with 50 iterations, 3-fold CV, optimizing for 'f1'...\n", "Fitting 3 folds for each of 50 candidates, totalling 150 fits\n", "\n", "Randomized Search Complete\n", "Best Score (f1) found: 0.9743\n", "Best Parameters found:\n", "{'subsample': 1.0, 'scale_pos_weight': 5, 'n_estimators': 900, 'max_depth': 7, 'learning_rate': 0.05, 'colsample_bytree': 0.7}\n" ] } ], "source": [ "xgb_base = xgb.XGBClassifier(\n", " objective = 'binary:logistic',\n", " eval_metric = 'logloss',\n", " use_label_encoder = False,\n", " random_state = 0\n", ")\n", "\n", "param_distributions = {\n", " 'n_estimators': [int(x) for x in np.linspace(start = 100, stop=1000, num=10)],\n", " 'max_depth': [3,4,5,6,7,8],\n", " 'learning_rate': [0.01, 0.05, 0.1, 0.2],\n", " 'scale_pos_weight': [5,10,15,20,24],\n", " 'subsample': [0.7,0.8,0.9,1.0],\n", " 'colsample_bytree': [0.7, 0.8, 0.9, 1.0]\n", "}\n", "\n", "n_iterations = 50\n", "\n", "cv_folds = 3\n", "\n", "scoring_metric = 'f1'\n", "\n", "print(f\"Starting Randomized Search with {n_iterations} iterations, {cv_folds}-fold CV, optimizing for '{scoring_metric}'...\")\n", "\n", "random_search = RandomizedSearchCV(\n", " estimator = xgb_base,\n", " param_distributions = param_distributions,\n", " n_iter = n_iterations,\n", " n_jobs = -1,\n", " cv = cv_folds,\n", " verbose = 1,\n", " random_state = 0\n", ")\n", "\n", "random_search.fit(X_train_est, y_train_est)\n", "\n", "print('\\nRandomized Search Complete')\n", "print(f\"Best Score ({scoring_metric}) found: {random_search.best_score_:.4f}\")\n", "print(\"Best Parameters found:\")\n", "print(random_search.best_params_)" ] }, { "cell_type": "markdown", "id": "6dc7fa27", "metadata": { "papermill": { "duration": 0.025759, "end_time": "2025-04-22T05:30:44.322650", "exception": false, "start_time": "2025-04-22T05:30:44.296891", "status": "completed" }, "tags": [] }, "source": [ "## Established Customer Final Model Evaluation and Interpretation" ] }, { "cell_type": "code", "execution_count": 53, "id": "94d9dfa3", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:30:44.374253Z", "iopub.status.busy": "2025-04-22T05:30:44.373865Z", "iopub.status.idle": "2025-04-22T05:30:46.849108Z", "shell.execute_reply": "2025-04-22T05:30:46.847961Z" }, "papermill": { "duration": 2.503086, "end_time": "2025-04-22T05:30:46.850832", "exception": false, "start_time": "2025-04-22T05:30:44.347746", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Evaluating the Best Tuned XGBoost Model on the Test Set...\n", "Evaluation Report for Established Customer Tuned XGB\n", " precision recall f1-score support\n", "\n", "No Churn (0) 0.98 1.00 0.99 67328\n", " Churn (1) 0.95 0.40 0.56 2810\n", "\n", " accuracy 0.98 70138\n", " macro avg 0.96 0.70 0.77 70138\n", "weighted avg 0.97 0.98 0.97 70138\n", "\n", "ROC AUC Score: 0.8292\n", "Precision-Recall Curve AUC (PRC AUC): 0.5149\n", "\n", " Confusion Matrix:\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "Comparison (Recall / Precision / F1 / PRC AUC / ROC AUC):\n", "Baseline RF: 0.32 / 0.59 / 0.42 / 0.4083 / 0.7615\n", "Tuned XGB: 0.40 / 0.95 / 0.56 / 0.5149 / 0.8292\n" ] } ], "source": [ "best_xgb_model = random_search.best_estimator_\n", "\n", "print(\"\\nEvaluating the Best Tuned XGBoost Model on the Test Set...\")\n", "tuned_xgb_metrics = evaluate_model(best_xgb_model, X_test_est, y_test_est, 'Established Customer Tuned XGB')\n", "\n", "print(\"\\nComparison (Recall / Precision / F1 / PRC AUC / ROC AUC):\")\n", "\n", "print(f\"Baseline RF: {baseline_metrics['Established RF']['recall_churn']:.2f} / {baseline_metrics['Established RF']['precision_churn']:.2f} / {baseline_metrics['Established RF']['f1_churn']:.2f} / {baseline_metrics['Established RF']['prc_auc']:.4f} / {baseline_metrics['Established RF']['roc_auc']:.4f}\")\n", "print(f\"Tuned XGB: {tuned_xgb_metrics['recall_churn']:.2f} / {tuned_xgb_metrics['precision_churn']:.2f} / {tuned_xgb_metrics['f1_churn']:.2f} / {tuned_xgb_metrics['prc_auc']:.4f} / {tuned_xgb_metrics['roc_auc']:.4f}\")" ] }, { "cell_type": "code", "execution_count": 54, "id": "eec2667e", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:30:46.903174Z", "iopub.status.busy": "2025-04-22T05:30:46.902817Z", "iopub.status.idle": "2025-04-22T05:30:47.320486Z", "shell.execute_reply": "2025-04-22T05:30:47.319382Z" }, "papermill": { "duration": 0.445932, "end_time": "2025-04-22T05:30:47.322462", "exception": false, "start_time": "2025-04-22T05:30:46.876530", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Top 20 Features by Importance (XGBoost Built-in):\n", " Feature Importance\n", "6 tenure_group_3-6mo 0.535142\n", "1 monthly_contact_rate 0.075205\n", "4 billing_cycles_completed 0.059344\n", "3 billing_cycle 0.053441\n", "8 tenure_group_1-2yr 0.051230\n", "2 price 0.046264\n", "7 tenure_group_6-12mo 0.037301\n", "0 days_since_last_contact 0.026869\n", "9 tenure_group_2yr+ 0.017336\n", "11 support_level_Low 0.017140\n", "10 product_prd_2 0.015845\n", "12 support_level_Medium 0.014056\n", "18 age_group_75+ 0.007627\n", "13 support_level_High 0.007614\n", "16 age_group_46-60 0.007538\n", "15 age_group_30-45 0.007509\n", "17 age_group_61-75 0.007499\n", "19 gender_male 0.007222\n", "5 recent_support 0.005816\n", "14 support_level_Very High 0.000000\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "importance_scores = best_xgb_model.feature_importances_\n", "\n", "feature_importance_df = pd.DataFrame({\n", " 'Feature': final_feature_names,\n", " 'Importance': importance_scores\n", "})\n", "\n", "feature_importance_df = feature_importance_df.sort_values(by='Importance', ascending=False)\n", "\n", "top_n = 20 \n", "print(f\"\\nTop {top_n} Features by Importance (XGBoost Built-in):\")\n", "print(feature_importance_df.head(top_n))\n", "\n", "plt.figure(figsize=(10, 8))\n", "sns.barplot(x='Importance', y='Feature', data=feature_importance_df.head(top_n), palette='viridis')\n", "plt.title(f'Top {top_n} Feature Importances - Tuned XGBoost (Established Customers)')\n", "plt.xlabel('Importance Score')\n", "plt.ylabel('Feature')\n", "plt.tight_layout() \n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 55, "id": "799e0683", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:30:47.379042Z", "iopub.status.busy": "2025-04-22T05:30:47.378690Z", "iopub.status.idle": "2025-04-22T05:30:47.395490Z", "shell.execute_reply": "2025-04-22T05:30:47.394480Z" }, "papermill": { "duration": 0.051875, "end_time": "2025-04-22T05:30:47.402246", "exception": false, "start_time": "2025-04-22T05:30:47.350371", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "shap.initjs()" ] }, { "cell_type": "code", "execution_count": 56, "id": "1d6e54ab", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:30:47.474053Z", "iopub.status.busy": "2025-04-22T05:30:47.473706Z", "iopub.status.idle": "2025-04-22T05:39:33.099535Z", "shell.execute_reply": "2025-04-22T05:39:33.098364Z" }, "papermill": { "duration": 525.697211, "end_time": "2025-04-22T05:39:33.135252", "exception": false, "start_time": "2025-04-22T05:30:47.438041", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Creating SHAP explainer...\n", "SHAP values calculated.\n" ] } ], "source": [ "print(\"Creating SHAP explainer...\")\n", "explainer = shap.TreeExplainer(best_xgb_model)\n", "\n", "try:\n", " if not isinstance(X_test_est, pd.DataFrame):\n", " X_test_est_df = pd.DataFrame(X_test_est, columns=final_feature_names) \n", " else:\n", " X_test_est_df = X_test_est\n", "\n", " shap_values = explainer.shap_values(X_test_est_df)\n", " print(\"SHAP values calculated.\")\n", "\n", "except Exception as e:\n", " print(f\"Error calculating SHAP values: {e}\")\n", " print(\"Ensure X_test_est is a pandas DataFrame or can be converted with final_feature_names.\")\n", " shap_values = None " ] }, { "cell_type": "code", "execution_count": 57, "id": "99bda74e", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:39:33.205620Z", "iopub.status.busy": "2025-04-22T05:39:33.205216Z", "iopub.status.idle": "2025-04-22T05:39:47.124358Z", "shell.execute_reply": "2025-04-22T05:39:47.123305Z" }, "papermill": { "duration": 13.956891, "end_time": "2025-04-22T05:39:47.126832", "exception": false, "start_time": "2025-04-22T05:39:33.169941", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "--- SHAP Summary Plots ---\n", "Generating SHAP Bar Plot (Mean Absolute SHAP Value)...\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "Generating SHAP Beeswarm Plot...\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "--- SHAP Dependence Plots (Examples) ---\n", "Generating SHAP Dependence Plot for 'monthly_contact_rate'...\n" ] }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Generating SHAP Dependence Plot for 'billing_cycles_completed'...\n" ] }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ " if shap_values is not None:\n", " print(\"\\n--- SHAP Summary Plots ---\")\n", " \n", " print(\"Generating SHAP Bar Plot (Mean Absolute SHAP Value)...\")\n", " plt.figure() # Create a new figure context\n", " shap.summary_plot(shap_values, X_test_est_df, plot_type=\"bar\", max_display=top_n, show=False)\n", " plt.title('SHAP Global Feature Importance (Bar Plot)')\n", " plt.tight_layout()\n", " plt.show()\n", " \n", " print(\"\\nGenerating SHAP Beeswarm Plot...\")\n", " plt.figure()\n", " shap.summary_plot(shap_values, X_test_est_df, max_display=top_n, show=False)\n", " plt.title('SHAP Feature Impact on Model Output (Beeswarm)') \n", " plt.tight_layout()\n", " plt.show()\n", "\n", " print(\"\\n--- SHAP Dependence Plots (Examples) ---\")\n", " \n", " top_feature_1 = 'monthly_contact_rate' \n", " top_feature_2 = 'billing_cycles_completed' \n", "\n", " try:\n", " print(f\"Generating SHAP Dependence Plot for '{top_feature_1}'...\")\n", " plt.figure()\n", " shap.dependence_plot(top_feature_1, shap_values, X_test_est_df, interaction_index=None, show=False) \n", " plt.title(f'SHAP Dependence Plot - {top_feature_1}')\n", " plt.tight_layout()\n", " plt.show()\n", "\n", " print(f\"Generating SHAP Dependence Plot for '{top_feature_2}'...\")\n", " plt.figure() # Create a new figure context\n", " shap.dependence_plot(top_feature_2, shap_values, X_test_est_df, interaction_index=\"auto\", show=False) # 'auto' tries to find interaction\n", " plt.title(f'SHAP Dependence Plot - {top_feature_2} (Interaction colored)')\n", " plt.tight_layout()\n", " plt.show()\n", "\n", " except Exception as e:\n", " print(f\"Could not generate one or more dependence plots: {e}\")\n", " print(\"Check if feature names exist exactly in X_test_est_df.columns\")\n", "\n", "else:\n", " print(\"Skipping SHAP plots due to calculation error.\")" ] }, { "cell_type": "markdown", "id": "a0f24be5", "metadata": { "papermill": { "duration": 0.045437, "end_time": "2025-04-22T05:39:47.218394", "exception": false, "start_time": "2025-04-22T05:39:47.172957", "status": "completed" }, "tags": [] }, "source": [ "### Revisit New Customer Model" ] }, { "cell_type": "code", "execution_count": 58, "id": "2959c650", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:39:47.309444Z", "iopub.status.busy": "2025-04-22T05:39:47.309100Z", "iopub.status.idle": "2025-04-22T05:39:47.328251Z", "shell.execute_reply": "2025-04-22T05:39:47.327141Z" }, "papermill": { "duration": 0.067124, "end_time": "2025-04-22T05:39:47.329966", "exception": false, "start_time": "2025-04-22T05:39:47.262842", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Overall rate of churn within first 90 days: 3.06%\n", "churned_within_90d\n", "0 493351\n", "1 15581\n", "Name: count, dtype: int64\n" ] } ], "source": [ "churn_df['churned_within_90d'] = (\n", " (churn_df['cancel_date_time'].notna()) &\n", " (churn_df['tenure_days'] < 90)\n", ").astype(int)\n", "\n", "new_churn_actual_rate = churn_df['churned_within_90d'].mean()\n", "print(f'Overall rate of churn within first 90 days: {new_churn_actual_rate:.2%}')\n", "print(churn_df['churned_within_90d'].value_counts())" ] }, { "cell_type": "code", "execution_count": 59, "id": "42c7a013", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:39:47.421778Z", "iopub.status.busy": "2025-04-22T05:39:47.421406Z", "iopub.status.idle": "2025-04-22T05:39:48.420941Z", "shell.execute_reply": "2025-04-22T05:39:48.419755Z" }, "papermill": { "duration": 1.047043, "end_time": "2025-04-22T05:39:48.422657", "exception": false, "start_time": "2025-04-22T05:39:47.375614", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "first_case_reason\n", "No_Contact 250272\n", "signup 129527\n", "support 129133\n", "Name: count, dtype: int64\n", "first_case_channel\n", "No_Contact 250272\n", "phone 230416\n", "email 28244\n", "Name: count, dtype: int64\n" ] } ], "source": [ "try: \n", " idx_first_case_per_customer = customer_cases.loc[customer_cases.groupby('customer_id')['date_time'].idxmin()]\n", " first_case_details = idx_first_case_per_customer[['customer_id', 'reason','channel']].rename(columns={\n", " 'reason':'first_case_reason',\n", " 'channel':'first_case_channel'\n", " })\n", "\n", " if 'first_case_reason' in churn_df.columns:\n", " churn_df = churn_df.drop(columns=['first_case_reaon'])\n", " if 'first_case_channel' in churn_df.columns:\n", " churn_df = churn_df.drop(columns=['first_case_channel'])\n", "\n", " churn_df = pd.merge(churn_df, first_case_details, on = 'customer_id', how = 'left')\n", " churn_df['first_case_reason'] = churn_df['first_case_reason'].fillna('No_Contact')\n", " churn_df['first_case_channel'] = churn_df['first_case_channel'].fillna('No_Contact')\n", "\n", " print(churn_df['first_case_reason'].value_counts())\n", " print(churn_df['first_case_channel'].value_counts())\n", "\n", "except KeyError as e:\n", " print(f\"Error: A required column is missing. Make sure 'customer_cases' DataFrame is loaded correctly. Error: {e}\")\n", "except Exception as e:\n", " print(f\"An unexpected error occurred during first case feature engineering: {e}\")" ] }, { "cell_type": "code", "execution_count": 60, "id": "a3273f1a", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:39:48.515489Z", "iopub.status.busy": "2025-04-22T05:39:48.515141Z", "iopub.status.idle": "2025-04-22T05:39:48.560190Z", "shell.execute_reply": "2025-04-22T05:39:48.559340Z" }, "papermill": { "duration": 0.093787, "end_time": "2025-04-22T05:39:48.561881", "exception": false, "start_time": "2025-04-22T05:39:48.468094", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "churn_df['signup_month'] = churn_df['signup_date_time'].dt.month\n", "churn_df['signup_day_of_week'] = churn_df['signup_date_time'].dt.dayofweek\n", "churn_df['contacted_within_7d'] = (churn_df['days_to_first_contact'] >= 0 & (churn_df['days_to_first_contact'] <= 7 )).astype(int)" ] }, { "cell_type": "code", "execution_count": 61, "id": "088999a1", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:39:48.652117Z", "iopub.status.busy": "2025-04-22T05:39:48.651743Z", "iopub.status.idle": "2025-04-22T05:39:48.866534Z", "shell.execute_reply": "2025-04-22T05:39:48.865167Z" }, "papermill": { "duration": 0.262271, "end_time": "2025-04-22T05:39:48.868275", "exception": false, "start_time": "2025-04-22T05:39:48.606004", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Columns available for new churn features: Index(['customer_id', 'product', 'signup_date_time', 'cancel_date_time',\n", " 'end_date', 'tenure_days', 'age', 'gender', 'product_id', 'name',\n", " 'price', 'billing_cycle', 'total_cases', 'first_case_date',\n", " 'last_case_date', 'days_between_cases', 'reasonsignup', 'reasonsupport',\n", " 'ever_contacted_support', 'will_churn_next_90d', 'days_since_signup',\n", " 'age_group', 'tenure_group', 'days_to_first_contact',\n", " 'churned_within_90d', 'first_case_reason', 'first_case_channel',\n", " 'signup_month', 'signup_day_of_week', 'contacted_within_7d'],\n", " dtype='object')\n", "\n", "Features selected for new Churn model (Revised):\n", "\n", "RangeIndex: 508932 entries, 0 to 508931\n", "Data columns (total 10 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 product 508932 non-null object \n", " 1 price 508932 non-null int64 \n", " 2 age_group 508932 non-null category\n", " 3 gender 508932 non-null object \n", " 4 signup_month 508932 non-null int32 \n", " 5 signup_day_of_week 508932 non-null int32 \n", " 6 contacted_within_7d 508932 non-null int64 \n", " 7 days_to_first_contact 508932 non-null float64 \n", " 8 first_case_reason 508932 non-null object \n", " 9 first_case_channel 508932 non-null object \n", "dtypes: category(1), float64(1), int32(2), int64(2), object(4)\n", "memory usage: 31.5+ MB\n", "None\n" ] } ], "source": [ "new_churn_features = [\n", " 'product',\n", " 'price',\n", " 'age_group',\n", " 'gender',\n", " 'signup_month',\n", " 'signup_day_of_week',\n", " 'contacted_within_7d',\n", " 'days_to_first_contact',\n", " 'first_case_reason',\n", " 'first_case_channel'\n", "]\n", "\n", "print('\\nColumns available for new churn features:', churn_df.columns)\n", "X_new = churn_df[new_churn_features].copy()\n", "y_new = churn_df['churned_within_90d']\n", "\n", "print('\\nFeatures selected for new Churn model (Revised):')\n", "print(X_new.info())" ] }, { "cell_type": "code", "execution_count": 62, "id": "42c949c7", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:39:48.959829Z", "iopub.status.busy": "2025-04-22T05:39:48.959465Z", "iopub.status.idle": "2025-04-22T05:39:49.139470Z", "shell.execute_reply": "2025-04-22T05:39:49.138264Z" }, "papermill": { "duration": 0.227851, "end_time": "2025-04-22T05:39:49.141363", "exception": false, "start_time": "2025-04-22T05:39:48.913512", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of features after dummification: 15\n", "First few new feature names: ['price', 'signup_month', 'signup_day_of_week', 'contacted_within_7d', 'days_to_first_contact', 'product_prd_2', 'age_group_30-45', 'age_group_46-60', 'age_group_61-75', 'age_group_75+']\n" ] } ], "source": [ "X_new_encoded = pd.get_dummies(X_new, drop_first = True, dummy_na = False)\n", "\n", "final_new_feature_names = X_new_encoded.columns.tolist()\n", "print(f'Number of features after dummification: {len(final_new_feature_names)}')\n", "print('First few new feature names:', final_new_feature_names[:10])" ] }, { "cell_type": "code", "execution_count": 63, "id": "721949d8", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:39:49.233872Z", "iopub.status.busy": "2025-04-22T05:39:49.233512Z", "iopub.status.idle": "2025-04-22T05:39:49.447810Z", "shell.execute_reply": "2025-04-22T05:39:49.446679Z" }, "papermill": { "duration": 0.262372, "end_time": "2025-04-22T05:39:49.449495", "exception": false, "start_time": "2025-04-22T05:39:49.187123", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Training set shape: (407145, 15)\n", "Testing set shape: (101787, 15)\n", "Training target distribution:\n", "churned_within_90d\n", "0 0.969384\n", "1 0.030616\n", "Name: proportion, dtype: float64\n", "Testing target distribution:\n", "churned_within_90d\n", "0 0.969387\n", "1 0.030613\n", "Name: proportion, dtype: float64\n" ] } ], "source": [ "X_train_new, X_test_new, y_train_new, y_test_new, = train_test_split(\n", " X_new_encoded,\n", " y_new,\n", " test_size = 0.20,\n", " random_state = 0,\n", " stratify = y_new\n", ")\n", "\n", "print(f'Training set shape: {X_train_new.shape}')\n", "print(f'Testing set shape: {X_test_new.shape}')\n", "print(f'Training target distribution:\\n{y_train_new.value_counts(normalize=True)}')\n", "print(f'Testing target distribution:\\n{y_test_new.value_counts(normalize=True)}')" ] }, { "cell_type": "markdown", "id": "6b52138a", "metadata": { "papermill": { "duration": 0.044864, "end_time": "2025-04-22T05:39:49.539624", "exception": false, "start_time": "2025-04-22T05:39:49.494760", "status": "completed" }, "tags": [] }, "source": [ "### New Customer XGBoost Model" ] }, { "cell_type": "code", "execution_count": 64, "id": "4828bec6", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:39:49.631238Z", "iopub.status.busy": "2025-04-22T05:39:49.630879Z", "iopub.status.idle": "2025-04-22T05:39:52.140497Z", "shell.execute_reply": "2025-04-22T05:39:52.139413Z" }, "papermill": { "duration": 2.55735, "end_time": "2025-04-22T05:39:52.142224", "exception": false, "start_time": "2025-04-22T05:39:49.584874", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Calculated scale_pos_weight for new Churn XGBoost: 31.66\n" ] }, { "data": { "text/html": [ "
XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
       "              colsample_bylevel=None, colsample_bynode=None,\n",
       "              colsample_bytree=None, device=None, early_stopping_rounds=None,\n",
       "              enable_categorical=False, eval_metric='logloss',\n",
       "              feature_types=None, gamma=None, grow_policy=None,\n",
       "              importance_type=None, interaction_constraints=None,\n",
       "              learning_rate=None, max_bin=None, max_cat_threshold=None,\n",
       "              max_cat_to_onehot=None, max_delta_step=None, max_depth=None,\n",
       "              max_leaves=None, min_child_weight=None, missing=nan,\n",
       "              monotone_constraints=None, multi_strategy=None, n_estimators=None,\n",
       "              n_jobs=None, num_parallel_tree=None, random_state=0, ...)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
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" ], "text/plain": [ "XGBClassifier(base_score=None, booster=None, callbacks=None,\n", " colsample_bylevel=None, colsample_bynode=None,\n", " colsample_bytree=None, device=None, early_stopping_rounds=None,\n", " enable_categorical=False, eval_metric='logloss',\n", " feature_types=None, gamma=None, grow_policy=None,\n", " importance_type=None, interaction_constraints=None,\n", " learning_rate=None, max_bin=None, max_cat_threshold=None,\n", " max_cat_to_onehot=None, max_delta_step=None, max_depth=None,\n", " max_leaves=None, min_child_weight=None, missing=nan,\n", " monotone_constraints=None, multi_strategy=None, n_estimators=None,\n", " n_jobs=None, num_parallel_tree=None, random_state=0, ...)" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "neg_count_new = (y_train_new == 0).sum()\n", "pos_count_new = (y_train_new == 1).sum()\n", "\n", "if pos_count_new > 0:\n", " scale_pos_weight_new = neg_count_new / pos_count_new\n", "else:\n", " scale_pos_weight_new = 1 \n", "\n", "print(f'\\nCalculated scale_pos_weight for new Churn XGBoost: {scale_pos_weight_new:.2f}')\n", "\n", "xgb_model_new = xgb.XGBClassifier(\n", " objective = 'binary:logistic',\n", " eval_metric = 'logloss',\n", " use_label_encoder = False,\n", " scale_pos_weight = scale_pos_weight_new,\n", " random_state = 0\n", ")\n", "\n", "xgb_model_new.fit(X_train_new, y_train_new)" ] }, { "cell_type": "code", "execution_count": 65, "id": "579ce360", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:39:52.237257Z", "iopub.status.busy": "2025-04-22T05:39:52.236768Z", "iopub.status.idle": "2025-04-22T05:39:53.911347Z", "shell.execute_reply": "2025-04-22T05:39:53.910286Z" }, "papermill": { "duration": 1.725418, "end_time": "2025-04-22T05:39:53.913092", "exception": false, "start_time": "2025-04-22T05:39:52.187674", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Evaluation Report for new Churn XGB Baseline\n", " precision recall f1-score support\n", "\n", "No Churn (0) 0.97 0.67 0.79 98671\n", " Churn (1) 0.04 0.42 0.07 3116\n", "\n", " accuracy 0.66 101787\n", " macro avg 0.51 0.55 0.43 101787\n", "weighted avg 0.94 0.66 0.77 101787\n", "\n", "ROC AUC Score: 0.5433\n", "Precision-Recall Curve AUC (PRC AUC): 0.0357\n", "\n", " Confusion Matrix:\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "Top 15 Features by Importance\n", " Feature Importance\n", "0 price 0.270229\n", "1 signup_month 0.066864\n", "2 signup_day_of_week 0.063876\n", "3 contacted_within_7d 0.061183\n", "4 days_to_first_contact 0.059339\n", "5 product_prd_2 0.000000\n", "6 age_group_30-45 0.055126\n", "7 age_group_46-60 0.061580\n", "8 age_group_61-75 0.065243\n", "9 age_group_75+ 0.051873\n", "10 gender_male 0.061767\n", "11 first_case_reason_signup 0.057988\n", "12 first_case_reason_support 0.000000\n", "13 first_case_channel_email 0.055668\n", "14 first_case_channel_phone 0.069265\n" ] }, { "data": { "image/png": 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nnyguLk4LFizI9y6BgtSsWVPu7u56++235eLiIicnJzVt2lS1a9dWzZo1NWbMGB07dkyurq5at25dvme7i+Ohhx5Sr1699PrrryslJUXt2rVTXl6eYmNj9dBDD2nYsGGqWbOmXn31VU2YMEGpqanq3LmzXFxc9Ntvv+mzzz7TwIEDNWbMGG3dulXDhg1Tly5dFBAQoMuXL+u9996TtbW1nnrqqVuOEQBMSuel6QAA4Eau/2SY0Wg0nj9/3jhy5Eijj4+P0dbW1lirVi3jnDlzTJ9IukqScejQocb333/fWKtWLaO9vb0xJCTEuG3btiLNffWzTQUd134O6qWXXjI2bNjQ6ObmZrS1tTVWrVrVOHjwYOPx48eLNE9Bn8i63qVLl4yzZ8821q1b12hvb28sX768sXHjxsYpU6YYMzIyTO02bNhgrF+/vtHBwcHo5+dnnD17tnH58uX5PqF1/Phx42OPPWZ0cXExSjL7fFh8fLyxadOmRjs7O2PVqlWN8+bNK/STYY899liB8Z4/f944YcIEo7+/v9HOzs5YoUIFY7NmzYxz5841fZ6rOPfj6s/yWlc/2zVnzhyz8m3btuX79NXVMffu3WsMCwszOjg4GKtVq2ZctGhRvvlPnDhh7Nu3r7FChQpGOzs7Y3BwcL7PfxU291Wff/65sU6dOkYbGxuz/14OHTpkbNOmjdHZ2dlYoUIF44ABA4wHDhzI999Unz59jE5OTvnGLeiTbpcvXzbOmTPHWLt2baOdnZ2xYsWKxvbt2xvj4+PN2q1bt87YvHlzo5OTk9HJyclYu3Zt49ChQ41JSUlGo9FoPHr0qLFfv37GmjVrGh0cHIweHh7Ghx56yPjdd98VeI0AUFwGo/E2vG0DAADcNgaDQUOHDs23FR33noiICJ06dUo///xzaYcCAPcsnukGAAAAAMBCSLoBAAAAALAQkm4AAAAAACyEZ7oBAAAAALAQVroBAAAAALAQkm4AAAAAACzEprQDAO4VeXl5+uuvv+Ti4iKDwVDa4QAAAAD4D4xGo86fPy8fHx9ZWRW+nk3SDdwmf/31l3x9fUs7DAAAAAAl6I8//tB9991XaD1JN3CbuLi4SLryP0pXV9dSjgYAAADAf5GZmSlfX1/T7/mFIekGbpOrW8pdXV1JugEAAIAy4maPjvIiNQAAAAAALISVbuA2C/BrJCsr69IOAwAAALjr/HUqqbRDKDZWugEAAAAAsBCSbgAAAAAALISkGwAAAAAACyHpBgAAAADAQki6AQAAAACwEJJuAAAAAAAshKQbAAAAAAALIenGPSk1NVUGg0H79+8v7VAAAAAAlGE2pR0AUBp8fX2Vnp6uChUqlHYoAAAAAMowkm7ccy5duiQ7OztVrly5tEMBAAAAUMaxvRx3vYiICA0bNkzDhg2Tm5ubKlSooIkTJ8poNEqS/Pz8NG3aNPXu3Vuurq4aOHBggdvLf/nlF3Xo0EGurq5ycXFRixYtdOTIEVP9u+++q6CgIDk4OKh27dp66623bvelAgAAALjLsNKNMmHlypXq37+/fvzxR+3du1cDBw5U1apVNWDAAEnS3LlzNWnSJL3yyisF9j927JgefPBBRUREaOvWrXJ1dVVcXJwuX74sSVq9erUmTZqkRYsWKSQkRAkJCRowYICcnJzUp0+fAsfMzs5Wdna26TwzM7OErxoAAADAnY6kG2WCr6+v5s+fL4PBoMDAQB08eFDz5883Jd2tWrXS6NGjTe1TU1PN+r/55ptyc3PTmjVrZGtrK0kKCAgw1b/yyiuKiorSk08+KUmqXr26Dh06pHfeeafQpHvmzJmaMmVKSV4mAAAAgLsM28tRJjzwwAMyGAym87CwMKWkpCg3N1eSFBoaesP++/fvV4sWLUwJ97WysrJ05MgR9e/fX87Ozqbj1VdfNdt+fr0JEyYoIyPDdPzxxx+3eHUAAAAA7lasdOOe4OTkdMN6R0fHQusuXLggSVq6dKmaNm1qVmdtbV1oP3t7e9nb2xcjSgAAAABlDUk3yoTdu3ebnf/www+qVavWDZPia9WvX18rV65UTk5OvtXuSpUqycfHR0ePHlXPnj1LLGYAAAAAZR/by1EmpKWladSoUUpKStKHH36oN954Qy+88EKR+w8bNkyZmZnq1q2b9u7dq5SUFL333ntKSkqSJE2ZMkUzZ87U66+/ruTkZB08eFArVqzQvHnzLHVJAAAAAMoAVrpRJvTu3Vv//POPmjRpImtra73wwgsaOHBgkft7enpq69atGjt2rFq2bClra2s1bNhQ4eHhkqRnn31W5cqV05w5czR27Fg5OTkpODhYI0aMsNAVAQAAACgLDMarHzMG7lIRERFq2LChFixYUNqh3FBmZqbc3NxUqXxNWVkVbds7AAAAgP/vr1NJpR2CydXf7zMyMuTq6lpoO7aXAwAAAABgISTdAAAAAABYCM904663ffv20g4BAAAAAArESjcAAAAAABZC0g0AAAAAgIWQdAMAAAAAYCEk3QAAAAAAWAgvUgNus+TUfTf8jh8AAACAsoOVbgAAAAAALISkGwAAAAAACyHpBgAAAADAQki6AQAAAACwEJJuAAAAAAAshLeXA7dZs6BWsrayLu0wgP/kwB+7SzsEAACAuwIr3QAAAAAAWAhJNwAAAAAAFkLSDQAAAACAhZB0AwAAAABgISTdAAAAAABYCEk3AAAAAAAWQtINAAAAAICFkHSXcZGRkercuXNph3HX2759uwwGg86dO1faoQAAAAC4i9iUdgCwrIULF8poNJZ2GHeViIgINWzYUAsWLCjtUAAAAADc5Ui6yzg3N7fSDgEAAAAA7llsLy8jPvnkEwUHB8vR0VGenp5q06aNsrKy8m0vP3/+vHr27CknJyd5e3tr/vz5ioiI0IgRI0xt/Pz8NGPGDPXr108uLi6qWrWqlixZYqovaKv1/v37ZTAYlJqaKkmKjo6Wu7u71q9fr1q1asnBwUFt27bVH3/8UaTrmTx5sho2bKjly5eratWqcnZ21pAhQ5Sbm6vXXntNlStXlpeXl6ZPn27WLy0tTZ06dZKzs7NcXV3VtWtXnThxIt+47733nvz8/OTm5qZu3brp/Pnzkq5sx4+JidHChQtlMBjMrkmS4uPjFRoaqnLlyqlZs2ZKSkoq0vUAAAAAuDeRdJcB6enp6t69u/r166fExERt375dTz75ZIHbykeNGqW4uDht2LBBmzdvVmxsrPbt25evXVRUlEJDQ5WQkKAhQ4Zo8ODBxU4wL168qOnTp2vVqlWKi4vTuXPn1K1btyL3P3LkiL755htt3LhRH374oZYtW6bHHntMf/75p2JiYjR79my9/PLL2r17tyQpLy9PnTp10pkzZxQTE6PNmzfr6NGjevrpp/ONu379en355Zf68ssvFRMTo1mzZkm6sh0/LCxMAwYMUHp6utLT0+Xr62vq+9JLLykqKkp79+6VjY2N+vXrV6x7AgAAAODewvbyMiA9PV2XL1/Wk08+qWrVqkmSgoOD87U7f/68Vq5cqQ8++ECtW7eWJK1YsUI+Pj752j766KMaMmSIJGn8+PGaP3++tm3bpsDAwCLHlZOTo0WLFqlp06aSpJUrVyooKEg//vijmjRpctP+eXl5Wr58uVxcXFSnTh099NBDSkpK0tdffy0rKysFBgZq9uzZ2rZtm5o2baotW7bo4MGD+u2330yJ8qpVq1S3bl3t2bNH999/v2nc6Ohoubi4SJJ69eqlLVu2aPr06XJzc5OdnZ3KlSunypUr54tp+vTpatmypSTpxRdf1GOPPaZ///1XDg4O+dpmZ2crOzvbdJ6ZmVnkewcAAACgbGCluwxo0KCBWrdureDgYHXp0kVLly7V2bNn87U7evSocnJyzBJeNze3AhPp+vXrm/5tMBhUuXJlnTx5slhx2djYmBJdSapdu7bc3d2VmJhYpP5+fn6mxFiSKlWqpDp16sjKysqs7GpciYmJ8vX1NVuZrlOnTr45rx/X29u7yNd27X3x9vaWpEL7zpw5U25ubqbj2rgAAAAA3BtIussAa2trbd68Wd98843q1KmjN954Q4GBgfrtt99ueUxbW1uzc4PBoLy8PEkyJb3Xbl/Pycm55bmKE8ON4vov4xZ1jGv7GgwGSSq074QJE5SRkWE6ivo8OwAAAICyg6S7jDAYDAoPD9eUKVOUkJAgOzs7ffbZZ2ZtatSoIVtbW+3Zs8dUlpGRoeTk5GLNVbFiRUlXtrVftX///nztLl++rL1795rOk5KSdO7cOQUFBRVrvqIKCgrSH3/8YZbcHjp0SOfOnVOdOnWKPI6dnZ1yc3P/czz29vZydXU1OwAAAADcW0i6y4Ddu3drxowZ2rt3r9LS0vTpp5/q77//zpfcuri4qE+fPho7dqy2bdumX375Rf3795eVlZVp1bYo/P395evrq8mTJyslJUVfffWVoqKi8rWztbXV888/r927dys+Pl6RkZF64IEHivQ8961o06aNgoOD1bNnT+3bt08//vijevfurZYtWyo0NLTI4/j5+Wn37t1KTU3VqVOnir2SDgAAAABXkXSXAa6urvr+++/16KOPKiAgQC+//LKioqLUvn37fG3nzZunsLAwdejQQW3atFF4eLiCgoIKfBFYYWxtbfXhhx/q8OHDql+/vmbPnq1XX301X7ty5cpp/Pjx6tGjh8LDw+Xs7KyPPvroP13rjRgMBn3++ecqX768HnzwQbVp00Y1atQo9pxjxoyRtbW16tSpo4oVKyotLc1CEQMAAAAo6wzGgr4rhXtGVlaWqlSpoqioKPXv37/Exo2OjtaIESPMvuV9r8vMzJSbm5vq+jSWtZV1aYcD/CcH/thd2iEAAACUqqu/32dkZNzwUVI+GXaPSUhI0OHDh9WkSRNlZGRo6tSpkqROnTqVcmQAAAAAUPawvfweNHfuXDVo0EBt2rRRVlaWYmNjVaFChdsaQ926deXs7FzgsXr16tsaCwAAAABYCtvLUSp+//33Qj8zVqlSJbPvaJcVbC9HWcL2cgAAcK9jeznuaNWqVSvtEAAAAADA4theDgAAAACAhZB0AwAAAABgISTdAAAAAABYCM90A7fZzsStN3zRAgAAAICyg5VuAAAAAAAshKQbAAAAAAALIekGAAAAAMBCSLoBAAAAALAQkm4AAAAAACyEpBsAAAAAAAvhk2HAbdaxweOyseJ/erizbTnyXWmHAAAAUCaw0g0AAAAAgIWQdAMAAAAAYCEk3QAAAAAAWAhJNwAAAAAAFkLSDQAAAACAhZB0AwAAAABgISTdAAAAAABYCEl3MURGRqpz586lHUaJmDx5sho2bFjaYZiJi4tTcHCwbG1t78j77OfnpwULFpR2GAAAAADuIjalHcDdZOHChTIajaUdRpk1atQoNWzYUN98842cnZ1LOxwAAAAA+M9Y6S4GNzc3ubu7l3YYZdaRI0fUqlUr3XfffdxnAAAAAGUCSXcBPvnkEwUHB8vR0VGenp5q06aNsrKy8m0vP3/+vHr27CknJyd5e3tr/vz5ioiI0IgRI0xt/Pz8NGPGDPXr108uLi6qWrWqlixZYqrfvn27DAaDzp07Zyrbv3+/DAaDUlNTJUnR0dFyd3fX+vXrVatWLTk4OKht27b6448/inxNs2bNUqVKleTi4qL+/fvr33//Navfs2ePHn74YVWoUEFubm5q2bKl9u3bZ6rv16+fOnToYNYnJydHXl5eWrZs2U3nz87O1vDhw+Xl5SUHBwc1b95ce/bskSSlpqbKYDDo9OnT6tevnwwGg6Kjo284XmhoqObOnWs679y5s2xtbXXhwgVJ0p9//imDwaBff/3VNP+YMWNUpUoVOTk5qWnTptq+fbvZmDt27FCLFi3k6OgoX19fDR8+XFlZWYXG8O6778rd3V1btmy56fUDAAAAuDeRdF8nPT1d3bt3V79+/ZSYmKjt27frySefLHBb+ahRoxQXF6cNGzZo8+bNio2NNUtUr4qKilJoaKgSEhI0ZMgQDR48WElJScWK6+LFi5o+fbpWrVqluLg4nTt3Tt26dStS37Vr12ry5MmaMWOG9u7dK29vb7311ltmbc6fP68+ffpox44d+uGHH1SrVi09+uijOn/+vCTp2Wef1caNG5Wenm7q8+WXX+rixYt6+umnbxrDuHHjtG7dOq1cuVL79u2Tv7+/2rZtqzNnzsjX11fp6elydXXVggULlJ6eftMxW7ZsaUqajUajYmNj5e7urh07dkiSYmJiVKVKFfn7+0uShg0bpl27dmnNmjX66aef1KVLF7Vr104pKSmSrqyyt2vXTk899ZR++uknffTRR9qxY4eGDRtW4PyvvfaaXnzxRX377bdq3bp1gW2ys7OVmZlpdgAAAAC4t5B0Xyc9PV2XL1/Wk08+KT8/PwUHB2vIkCH5njE+f/68Vq5cqblz56p169aqV6+eVqxYodzc3HxjPvrooxoyZIj8/f01fvx4VahQQdu2bStWXDk5OVq0aJHCwsLUuHFjrVy5Ujt37tSPP/54074LFixQ//791b9/fwUGBurVV19VnTp1zNq0atVKzzzzjGrXrq2goCAtWbJEFy9eVExMjCSpWbNmCgwM1HvvvWfqs2LFCnXp0uWmz19nZWVp8eLFmjNnjtq3b686depo6dKlcnR01LJly2Rtba3KlSvLYDDIzc1NlStXlqOj4w3HjIiI0I4dO5Sbm6uffvpJdnZ26tmzpykR3759u1q2bClJSktL04oVK/Txxx+rRYsWqlmzpsaMGaPmzZtrxYoVkqSZM2eqZ8+eGjFihGrVqqVmzZrp9ddf16pVq/LtChg/frwWLFigmJgYNWnSpNAYZ86cKTc3N9Ph6+t7w2sCAAAAUPaQdF+nQYMGat26tYKDg9WlSxctXbpUZ8+ezdfu6NGjysnJMUu63NzcFBgYmK9t/fr1Tf82GAyqXLmyTp48Way4bGxsdP/995vOa9euLXd3dyUmJt60b2Jiopo2bWpWFhYWZnZ+4sQJDRgwQLVq1ZKbm5tcXV114cIFpaWlmdo8++yzpiT1xIkT+uabb9SvX7+bzn/kyBHl5OQoPDzcVGZra6smTZoUKf6CtGjRQufPn1dCQoJiYmLUsmVLRUREmJLumJgYRURESJIOHjyo3NxcBQQEyNnZ2XTExMToyJEjkqQDBw4oOjrarL5t27bKy8vTb7/9Zpo3KipKS5cu1Y4dO1S3bt0bxjhhwgRlZGSYjuI8DgAAAACgbODt5dextrbW5s2btXPnTn377bd644039NJLL2n37t23PKatra3ZucFgUF5eniTJyurK3z2u3b6ek5Nzy3Pdqj59+uj06dNauHChqlWrJnt7e4WFhenSpUumNr1799aLL76oXbt2aefOnapevbpatGhx22OVJHd3dzVo0EDbt2/Xrl279PDDD+vBBx/U008/reTkZKWkpJhWui9cuCBra2vFx8fL2trabJyrq/QXLlzQc889p+HDh+ebq2rVqqZ/t2jRQl999ZXWrl2rF1988YYx2tvby97e/r9eKgAAAIC7GCvdBTAYDAoPD9eUKVOUkJAgOzs7ffbZZ2ZtatSoIVtbW9PLwCQpIyNDycnJxZqrYsWKkmT2rPT+/fvztbt8+bL27t1rOk9KStK5c+cUFBR00zmCgoLy/dHghx9+MDuPi4vT8OHD9eijj6pu3bqyt7fXqVOnzNp4enqqc+fOWrFihaKjo9W3b9+bzi1JNWvWlJ2dneLi4kxlOTk52rNnT75t7sXRsmVLbdu2Td9//70iIiLk4eGhoKAgTZ8+Xd7e3goICJAkhYSEKDc3VydPnpS/v7/ZUblyZUlSo0aNdOjQoXz1/v7+srOzM83ZpEkTffPNN5oxY4bZi9wAAAAAoCCsdF9n9+7d2rJlix555BF5eXlp9+7d+vvvvxUUFKSffvrJ1M7FxUV9+vTR2LFj5eHhIS8vL73yyiuysrKSwWAo8nz+/v7y9fXV5MmTNX36dCUnJysqKipfO1tbWz3//PN6/fXXZWNjo2HDhumBBx644TPFV73wwguKjIxUaGiowsPDtXr1av3yyy+qUaOGqU2tWrX03nvvKTQ0VJmZmRo7dmyBz1U/++yz6tChg3Jzc9WnT58iXaOTk5MGDx5suldVq1bVa6+9posXL6p///5FGqMgEREReuONN1SxYkXVrl3bVLZo0SJ16dLF1C4gIEA9e/ZU7969FRUVpZCQEP3999/asmWL6tevr8cee0zjx4/XAw88oGHDhunZZ5+Vk5OTDh06pM2bN2vRokVm8zZr1kxff/212rdvLxsbG7O31QMAAADAtVjpvo6rq6u+//57PfroowoICNDLL7+sqKgotW/fPl/befPmKSwsTB06dFCbNm0UHh6uoKAgOTg4FHk+W1tbffjhhzp8+LDq16+v2bNn69VXX83Xrly5cho/frx69Oih8PBwOTs766OPPirSHE8//bQmTpyocePGqXHjxvr99981ePBgszbLli3T2bNn1ahRI/Xq1cv0ea/rtWnTRt7e3mrbtq18fHyKfJ2zZs3SU089pV69eqlRo0b69ddftWnTJpUvX77IY1yvRYsWysvLM20jl64k3bm5uabnua9asWKFevfurdGjRyswMFCdO3fWnj17TFvH69evr5iYGCUnJ6tFixYKCQnRpEmTCr3G5s2b66uvvtLLL7+sN95445avAQAAAEDZZjAW9C0s3JKsrCxVqVJFUVFR/2kF93rR0dEaMWKE2be8S8uFCxdUpUoVrVixQk8++WRph3NXyczMlJubmx70aykbKzaZ4M625ch3pR0CAADAHe3q7/cZGRlydXUttB2/+f8HCQkJOnz4sJo0aaKMjAxNnTpVktSpU6dSjqzk5eXl6dSpU4qKipK7u7sef/zx0g4JAAAAAO54bC//j+bOnasGDRqoTZs2ysrKUmxsrCpUqHBbY6hbt67Zp66uPVavXl0ic6SlpalSpUr64IMPtHz5ctnY2JjVFTa/s7Oz2WfHimrQoEGFjjdo0KASuSYAAAAAsDS2l5cBv//+e6GfGatUqZJcXFwsOv/ly5eVmppaaL2fn59Zkl4UJ0+eVGZmZoF1rq6uBT5vfqdjeznuJmwvBwAAuDG2l99DqlWrVqrz29jYyN/fv0TH9PLyuisTawAAAAC4FtvLAQAAAACwEJJuAAAAAAAshKQbAAAAAAAL4Zlu4Db74sCGG75oAQAAAEDZwUo3AAAAAAAWQtINAAAAAICFkHQDAAAAAGAhJN0AAAAAAFgISTcAAAAAABZC0g0AAAAAgIXwyTDgNuvfuJtsrW1LOwxAHxz+vLRDAAAAKPNY6QYAAAAAwEJIugEAAAAAsBCSbgAAAAAALISkGwAAAAAACyHpBgAAAADAQki6AQAAAACwEJJuAAAAAAAshKQb+aSmpspgMGj//v0lPrafn58WLFhwwzaTJ09Ww4YNb9gmIiJCI0aMKLG4bkV0dLTc3d1LNQYAAAAAdzaS7lJQlMSzuCyZKJekPXv2aODAgaZzg8Gg9evXF3ucTz/9VNOmTSuRmLZv3y6DwVDgsWfPnhKZAwAAAMC9yaa0A8C9pWLFiiUyjoeHR4mMI0nNmjVTenq6WdnEiRO1ZcsWhYaGltg8AAAAAO49rHQXIC8vT6+99pr8/f1lb2+vqlWravr06ZKkgwcPqlWrVnJ0dJSnp6cGDhyoCxcumPpGRkaqc+fOmjt3rry9veXp6amhQ4cqJydH0pVt0b///rtGjhxpWk2VpNOnT6t79+6qUqWKypUrp+DgYH344YdFjqt69eqSpJCQEBkMBkVERJj6vfvuuwoKCpKDg4Nq166tt956y2zcH3/8USEhIXJwcFBoaKgSEhKKfK9CQ0M1d+5c03nnzp1la2truid//vmnDAaDfv31V0nmq/x+fn6SpCeeeEIGg8F0ftV7770nPz8/ubm5qVu3bjp//ryp7vrt5X5+fpoxY4b69esnFxcXVa1aVUuWLCnSNdjZ2aly5cqmw9PTU59//rn69u1r+vlIV7aTV61aVeXKldMTTzyh06dPF/U2AQAAALhHkXQXYMKECZo1a5YmTpyoQ4cO6YMPPlClSpWUlZWltm3bqnz58tqzZ48+/vhjfffddxo2bJhZ/23btunIkSPatm2bVq5cqejoaEVHR0u6si36vvvu09SpU5Wenm5aYf3333/VuHFjffXVV/r55581cOBA9erVSz/++ONN45Jkavfdd98pPT1dn376qSRp9erVmjRpkqZPn67ExETNmDFDEydO1MqVKyVJFy5cUIcOHVSnTh3Fx8dr8uTJGjNmTJHvVcuWLbV9+3ZJktFoVGxsrNzd3bVjxw5JUkxMjKpUqSJ/f/98fa9u3V6xYoXS09PNtnIfOXJE69ev15dffqkvv/xSMTExmjVr1g1jiYqKMv3RYMiQIRo8eLCSkpKKfC1XbdiwQadPn1bfvn1NZbt371b//v01bNgw7d+/Xw899JBeffXVG46TnZ2tzMxMswMAAADAvYXt5dc5f/68Fi5cqEWLFqlPnz6SpJo1a6p58+ZaunSp/v33X61atUpOTk6SpEWLFqljx46aPXu2KQEuX768Fi1aJGtra9WuXVuPPfaYtmzZogEDBsjDw0PW1tZycXFR5cqVTfNWqVLFLNl9/vnntWnTJq1du1ZNmjS5YVzS/9+27enpaTbuK6+8oqioKD355JOSrqyIHzp0SO+884769OmjDz74QHl5eVq2bJkcHBxUt25d/fnnnxo8eHCR7ldERISWLVum3Nxc/fzzz7Kzs9PTTz+t7du3q127dtq+fbtatmxZYN+rMbu7u5vFLF1Z1Y+OjpaLi4skqVevXtqyZYtpZb8gjz76qIYMGSJJGj9+vObPn69t27YpMDCwSNdy1bJly9S2bVvdd999prKFCxeqXbt2GjdunCQpICBAO3fu1MaNGwsdZ+bMmZoyZUqx5gYAAABQtrDSfZ3ExERlZ2erdevWBdY1aNDAlHBLUnh4uPLy8sxWVOvWrStra2vTube3t06ePHnDeXNzczVt2jQFBwfLw8NDzs7O2rRpk9LS0m4aV2GysrJ05MgR9e/fX87Ozqbj1Vdf1ZEjR0zj1q9fXw4ODqZ+YWFhRZ6jRYsWOn/+vBISEhQTE6OWLVsqIiLCtPodExNjttW9qPz8/EwJt1S0e1i/fn3Tvw0GgypXrnzTPtf7888/tWnTJvXv39+sPDExUU2bNjUru9l9mjBhgjIyMkzHH3/8UaxYAAAAANz9WOm+jqOj438ew9bW1uzcYDAoLy/vhn3mzJmjhQsXasGCBQoODpaTk5NGjBihS5cu3XJcV5+rXrp0ab6E8do/CvwX7u7uatCggbZv365du3bp4Ycf1oMPPqinn35aycnJSklJKXSl+0Zu5R7eSp/rrVixQp6ennr88ceL1a8g9vb2sre3/8/jAAAAALh7sdJ9nVq1asnR0VFbtmzJVxcUFKQDBw4oKyvLVBYXFycrK6tibWG2s7NTbm6uWVlcXJw6deqkZ555Rg0aNFCNGjWUnJxcpLiujinJbNxKlSrJx8dHR48elb+/v9lx9cVrQUFB+umnn/Tvv/+a+v3www9FvhbpynPd27Zt0/fff6+IiAh5eHgoKChI06dPl7e3twICAgrta2trm+9elBaj0agVK1aod+/e+RL4oKAg7d6926ysuPcJAAAAwL2HpPs6Dg4OGj9+vMaNG6dVq1bpyJEj+uGHH7Rs2TL17NlTDg4O6tOnj37++Wdt27ZNzz//vHr16mV6nrso/Pz89P333+vYsWM6deqUpCtJ9ebNm7Vz504lJibqueee04kTJ4oUlyR5eXnJ0dFRGzdu1IkTJ5SRkSFJmjJlimbOnKnXX39dycnJOnjwoFasWKF58+ZJknr06CGDwaABAwbo0KFD+vrrr83eRl4UERER2rRpk2xsbFS7dm1T2erVq2+6yu3n56ctW7bo+PHjOnv2bLHmLWlbt27Vb7/9pmeffTZf3fDhw7Vx40bNnTtXKSkpWrRo0Q2f5wYAAAAAiaS7QBMnTtTo0aM1adIkBQUF6emnn9bJkydVrlw5bdq0SWfOnNH999+v//3vf2rdurUWLVpUrPGnTp2q1NRU1axZ0/QysZdfflmNGjVS27ZtFRERocqVK6tz585FikuSbGxs9Prrr+udd96Rj4+POnXqJEl69tln9e6772rFihUKDg5Wy5YtFR0dbVrpdnZ21hdffKGDBw8qJCREL730kmbPnl2s62nRooXy8vLMEuyIiAjl5ube9HnuqKgobd68Wb6+vgoJCSnWvCVt2bJlatasmekPB9d64IEHtHTpUi1cuFANGjTQt99+q5dffrkUogQAAABwNzEYjUZjaQcB3AsyMzPl5uam//m3l6217c07ABb2weHPSzsEAACAu9bV3+8zMjLk6upaaDtWugEAAAAAsBCSbtzQoEGDzD43du0xaNCg0g6vSGbMmFHoNbRv3760wwMAAABQhrG9HDd08uRJZWZmFljn6uoqLy+v2xxR8Z05c0ZnzpwpsM7R0VFVqlS5LXGwvRx3GraXAwAA3Lqibi/nO924IS8vr7sisb4RDw8PeXh4lHYYAAAAAO5BbC8HAAAAAMBCSLoBAAAAALAQtpcDt9my+DU3fOYDAAAAQNnBSjcAAAAAABZC0g0AAAAAgIWQdAMAAAAAYCEk3QAAAAAAWAhJNwAAAAAAFkLSDQAAAACAhfDJMOA2e7FJpOytbUs7DNxj5v/yUWmHAAAAcE9ipRsAAAAAAAsh6QYAAAAAwEJIugEAAAAAsBCSbgAAAAAALISkGwAAAAAACyHpBgAAAADAQki6AQAAAACwEJLuQkRERGjEiBGlHYZFXLx4UU899ZRcXV1lMBh07tw5+fn5acGCBaUdGgAAAACUKSTddzhLJMMrV65UbGysdu7cqfT0dLm5uWnPnj0aOHDgLY+Zmpoqg8Gg/fv3l1ygJcBSfzwxGAxav359iY8LAAAAoGyxKe0AcPsdOXJEQUFBqlevnqmsYsWKN+yTk5MjW1tbS4cGAAAAAGUKK92SsrKy1Lt3bzk7O8vb21tRUVFm9e+9955CQ0Pl4uKiypUrq0ePHjp58qQkyWg0yt/fX3PnzjXrs3//fhkMBv36668yGo2aPHmyqlatKnt7e/n4+Gj48OE3jSsiIkK///67Ro4cKYPBIIPBYKpbt26d6tatK3t7e/n5+eWL+UZjRkVF6fvvv5fBYFBERISk/CvqBoNBixcv1uOPPy4nJydNnz5dZ8+eVc+ePVWxYkU5OjqqVq1aWrFihSSpevXqkqSQkBCzcW9m+fLlpuvw9vbWsGHDTHVpaWnq1KmTnJ2d5erqqq5du+rEiROm+smTJ6thw4Z677335OfnJzc3N3Xr1k3nz5+XJEVGRiomJkYLFy403b/U1FTl5uaqf//+ql69uhwdHRUYGKiFCxcWOTY/Pz9J0hNPPCGDwWA6BwAAAIDrkXRLGjt2rGJiYvT555/r22+/1fbt27Vv3z5TfU5OjqZNm6YDBw5o/fr1Sk1NVWRkpKQryWm/fv1MyedVK1as0IMPPih/f3+tW7dO8+fP1zvvvKOUlBStX79ewcHBN43r008/1X333aepU6cqPT1d6enpkqT4+Hh17dpV3bp108GDBzV58mRNnDhR0dHRRRpzwIABCgsLU3p6uj799NNC206ePFlPPPGEDh48qH79+mnixIk6dOiQvvnmGyUmJmrx4sWqUKGCJOnHH3+UJH333Xc3HfeqxYsXa+jQoRo4cKAOHjyoDRs2yN/fX5KUl5enTp066cyZM4qJidHmzZt19OhRPf3002ZjHDlyROvXr9eXX36pL7/8UjExMZo1a5YkaeHChQoLC9OAAQNM98/X11d5eXm677779PHHH+vQoUOaNGmS/u///k9r164tUmx79uyRdOVnnJ6ebjoHAAAAgOvd89vLL1y4oGXLlun9999X69atJV155vm+++4ztenXr5/p3zVq1NDrr7+u+++/XxcuXJCzs7MiIyM1adIk/fjjj2rSpIlycnL0wQcfmFa/09LSVLlyZbVp00a2traqWrWqmjRpctPYPDw8ZG1tbVphv2revHlq3bq1Jk6cKEkKCAjQoUOHNGfOHNMfA240Zrly5WRnZ2c2ZkF69Oihvn37ms7T0tIUEhKi0NBQSTJb4b26Pd3T0/Om41716quvavTo0XrhhRdMZffff78kacuWLTp48KB+++03+fr6SpJWrVqlunXras+ePaZ2eXl5io6OlouLiySpV69e2rJli6ZPny43NzfZ2dmpXLlyZjFZW1trypQppvPq1atr165dWrt2rbp27XrT2K5eq7u7+w2vNTs7W9nZ2abzzMzMIt0XAAAAAGXHPb/SfeTIEV26dElNmzY1lXl4eCgwMNB0Hh8fr44dO6pq1apycXFRy5YtJV1JQiXJx8dHjz32mJYvXy5J+uKLL5Sdna0uXbpIkrp06aJ//vlHNWrU0IABA/TZZ5/p8uXLtxxzYmKiwsPDzcrCw8OVkpKi3NzcWx73eleT66sGDx6sNWvWqGHDhho3bpx27tx5y2OfPHlSf/31l+kPHddLTEyUr6+vKeGWpDp16sjd3V2JiYmmMj8/P1PCLUne3t6mrf838uabb6px48aqWLGinJ2dtWTJEtPP82axFdXMmTPl5uZmOq69FgAAAAD3hns+6b6ZrKwstW3bVq6urlq9erX27Nmjzz77TJJ06dIlU7tnn31Wa9as0T///KMVK1bo6aefVrly5SRJvr6+SkpK0ltvvSVHR0cNGTJEDz74oHJyckrlmorKycnJ7Lx9+/amZ8yvJqVjxoy5pbEdHR1LIsR8L3czGAzKy8u7YZ81a9ZozJgx6t+/v7799lvt379fffv2Nf08Syq2CRMmKCMjw3T88ccfJTIuAAAAgLvHPZ9016xZU7a2ttq9e7ep7OzZs0pOTpYkHT58WKdPn9asWbPUokUL1a5du8CV1EcffVROTk5avHixNm7caLYlXbqSyHXs2FGvv/66tm/frl27dungwYM3jc/Ozi7f6nVQUJDi4uLMyuLi4hQQECBra+siX/utqFixovr06aP3339fCxYs0JIlS0xxSirySruLi4v8/Py0ZcuWAuuDgoL0xx9/mCWqhw4d0rlz51SnTp0ix1vQ/YuLi1OzZs00ZMgQhYSEyN/fX0eOHClybNKVZP9m12pvby9XV1ezAwAAAMC95Z5/ptvZ2Vn9+/fX2LFj5enpKS8vL7300kuysrry94iqVavKzs5Ob7zxhgYNGqSff/5Z06ZNyzeOtbW1IiMjNWHCBNWqVUthYWGmuujoaOXm5qpp06YqV66c3n//fTk6OqpatWo3jc/Pz0/ff/+9unXrJnt7e1WoUEGjR4/W/fffr2nTpunpp5/Wrl27tGjRIr311lsld2MKMGnSJDVu3Fh169ZVdna2vvzySwUFBUmSvLy85OjoqI0bN+q+++6Tg4OD3Nzcbjje5MmTNWjQIHl5eal9+/Y6f/684uLi9Pzzz6tNmzYKDg5Wz549tWDBAl2+fFlDhgxRy5Yt8217vxE/Pz/t3r1bqampcnZ2loeHh2rVqqVVq1Zp06ZNql69ut577z3t2bPH9Ab2m8V2ddwtW7YoPDxc9vb2Kl++/C3cUQAAAABl3T2/0i1Jc+bMUYsWLdSxY0e1adNGzZs3V+PGjSVdWdmNjo7Wxx9/rDp16mjWrFn5Pg92Vf/+/XXp0iWzl49JV164tXTpUoWHh6t+/fr67rvv9MUXX8jT0/OmsU2dOlWpqamqWbOm6QVejRo10tq1a7VmzRrVq1dPkyZN0tSpU2/6ErX/ys7OThMmTFD9+vX14IMPytraWmvWrJEk2djY6PXXX9c777wjHx8fderU6abj9enTRwsWLNBbb72lunXrqkOHDkpJSZF0ZZv4559/rvLly+vBBx9UmzZtVKNGDX300UfFinnMmDGytrZWnTp1VLFiRaWlpem5557Tk08+qaefflpNmzbV6dOnNWTIkCLHJklRUVHavHmzfH19FRISUqyYAAAAANw7DEaj0VjaQZQVsbGxat26tf744w9VqlSptMPBHSYzM1Nubm4aHPiE7K1tb94BKEHzfyneH6wAAABwY1d/v8/IyLjho6T3/PbykpCdna2///5bkydPVpcuXUi4AQAAAACS2F5eIj788ENVq1ZN586d02uvvVbkfrGxsXJ2di70uBWWGPNW3SiO2NjY2xoLAAAAAJQGtpeXon/++UfHjh0rtN7f3/+OGPNW/frrr4XWValSpcQ+zXW3YHs5ShPbywEAAEoW28vvAo6OjiWeBFtizFt1p8QBAAAAAKWF7eUAAAAAAFgISTcAAAAAABZC0g0AAAAAgIXwTDdwm836MfqGL1oAAAAAUHaw0g0AAAAAgIWQdAMAAAAAYCEk3QAAAAAAWAhJNwAAAAAAFkLSDQAAAACAhZB0AwAAAABgISTdAAAAAABYCEk3AAAAAAAWQtINAAAAAICFkHQDAAAAAGAhJN0AAAAAAFgISTcAAAAAABZC0g0AAAAAgIWQdAMAAAAAYCEk3SgyPz8/LViwoLTDKDEREREaMWJEaYcBAAAAoAwj6UapiYyMVOfOnUs7jJvKycnR+PHjFRwcLCcnJ/n4+Kh3797666+/Sjs0AAAAAHc4ku57zKVLl0o7hNvKaDTq8uXL/2mMixcvat++fZo4caL27dunTz/9VElJSXr88cdLKEoAAAAAZRVJ910uIiJCw4YN07Bhw+Tm5qYKFSpo4sSJMhqNkq5sCZ82bZp69+4tV1dXDRw4UJK0bt061a1bV/b29vLz81NUVJTZuCdPnlTHjh3l6Oio6tWra/Xq1Wb1qampMhgM2r9/v6ns3LlzMhgM2r59u6nsl19+UYcOHeTq6ioXFxe1aNFCR44c0eTJk7Vy5Up9/vnnMhgM+foV5Oqca9asUbNmzeTg4KB69eopJibG1Gb79u0yGAz65ptv1LhxY9nb22vHjh3KyspS79695ezsLG9v73zXeyNubm7avHmzunbtqsDAQD3wwANatGiR4uPjlZaWVuRxAAAAANx7bEo7APx3K1euVP/+/fXjjz9q7969GjhwoKpWraoBAwZIkubOnatJkybplVdekSTFx8era9eumjx5sp5++mnt3LlTQ4YMkaenpyIjIyVd2fr9119/adu2bbK1tdXw4cN18uTJYsV17NgxPfjgg4qIiNDWrVvl6uqquLg4Xb58WWPGjFFiYqIyMzO1YsUKSZKHh0eRxh07dqwWLFigOnXqaN68eerYsaN+++03eXp6mtq8+OKLmjt3rmrUqKHy5ctr7NixiomJ0eeffy4vLy/93//9n/bt26eGDRsW65quysjIkMFgkLu7e6FtsrOzlZ2dbTrPzMy8pbkAAAAA3L1IussAX19fzZ8/XwaDQYGBgTp48KDmz59vSrpbtWql0aNHm9r37NlTrVu31sSJEyVJAQEBOnTokObMmaPIyEglJyfrm2++0Y8//qj7779fkrRs2TIFBQUVK64333xTbm5uWrNmjWxtbU1zXeXo6Kjs7GxVrly5WOMOGzZMTz31lCRp8eLF2rhxo5YtW6Zx48aZ2kydOlUPP/ywJOnChQtatmyZ3n//fbVu3VrSlT9U3HfffcWa96p///1X48ePV/fu3eXq6lpou5kzZ2rKlCm3NAcAAACAsoHt5WXAAw88IIPBYDoPCwtTSkqKcnNzJUmhoaFm7RMTExUeHm5WFh4ebuqTmJgoGxsbNW7c2FRfu3btG67qFmT//v1q0aKFKeEuKWFhYaZ/29jYKDQ0VImJiWZtrr3mI0eO6NKlS2ratKmpzMPDQ4GBgcWeOycnR127dpXRaNTixYtv2HbChAnKyMgwHX/88Uex5wMAAABwd2Ol+x7g5ORU4mNaWV35e83VZ8elKwnptRwdHUt83qKyxDVfTbh///1303b5G7G3t5e9vX2JxwEAAADg7sFKdxmwe/dus/MffvhBtWrVkrW1dYHtg4KCFBcXZ1YWFxengIAAWVtbq3bt2rp8+bLi4+NN9UlJSTp37pzpvGLFipKk9PR0U9m1L1WTpPr16ys2NjZfMn6VnZ2daTW+OH744QfTv6/GeaOt7zVr1pStra3ZfTp79qySk5OLPOfVhDslJUXfffed2fPjAAAAAFAYku4yIC0tTaNGjVJSUpI+/PBDvfHGG3rhhRcKbT969Ght2bJF06ZNU3JyslauXKlFixZpzJgxkqTAwEC1a9dOzz33nHbv3q34+Hg9++yzZivXjo6OeuCBBzRr1iwlJiYqJiZGL7/8stk8w4YNU2Zmprp166a9e/cqJSVF7733npKSkiRdebP6Tz/9pKSkJJ06darQ5Px6b775pj777DMdPnxYQ4cO1dmzZ9WvX79C2zs7O6t///4aO3astm7dqp9//lmRkZGm1fqbycnJ0f/+9z/t3btXq1evVm5uro4fP67jx4/fc59gAwAAAFA8JN1lQO/evfXPP/+oSZMmGjp0qF544QXTp8EK0qhRI61du1Zr1qxRvXr1NGnSJE2dOtX05nJJWrFihXx8fNSyZUs9+eSTGjhwoLy8vMzGWb58uS5fvqzGjRtrxIgRevXVV83qPT09tXXrVl24cEEtW7ZU48aNtXTpUtMz3gMGDFBgYKBCQ0NVsWLFfKvvhZk1a5ZmzZqlBg0aaMeOHdqwYYMqVKhwwz5z5sxRixYt1LFjR7Vp00bNmzc3e2b9Ro4dO6YNGzbozz//VMOGDeXt7W06du7cWaQxAAAAANybDMZrH8rFXSciIkINGzbUggULSjsUi0tNTVX16tWVkJBwy5/6Kk2ZmZlyc3NTRkbGTZ8HBwAAAHBnK+rv96x0AwAAAABgISTduGPMmDFDzs7OBR7t27e32LyxsbGFzuvs7GyxeQEAAACUfWwvxx3jzJkzOnPmTIF1jo6OqlKlikXm/eeff3Ts2LFC6/39/UtkHraXAwAAAGVHUX+/5zvduGN4eHjIw8Pjts/r6OhYYok1AAAAAFyL7eUAAAAAAFgISTcAAAAAABZC0g0AAAAAgIWQdAMAAAAAYCEk3QAAAAAAWAhJNwAAAAAAFkLSDQAAAACAhZB0AwAAAABgISTdAAAAAABYiE1pBwDca1Y3GSBHa9vSDgN3uchf3i/tEAAAAFAErHQDAAAAAGAhJN0AAAAAAFgISTcAAAAAABZC0g0AAAAAgIWQdAMAAAAAYCEk3QAAAAAAWAhJNwAAAAAAFkLSDQAAAACAhZB0465x+vRptWvXTj4+PrK3t5evr6+GDRumzMxMs3bbt29Xo0aNZG9vL39/f0VHRxdrnkGDBslgMGjBggVm5X5+fjIYDGbHrFmz/uNVAQAAACjLSLpxU5cuXSrtECRJVlZW6tSpkzZs2KDk5GRFR0fru+++06BBg0xtfvvtNz322GN66KGHtH//fo0YMULPPvusNm3aVKQ5PvvsM/3www/y8fEpsH7q1KlKT083Hc8//3yJXBsAAACAsomk+zbbuHGjmjdvLnd3d3l6eqpDhw46cuSIqX7nzp1q2LChHBwcFBoaqvXr18tgMGj//v2mNj///LPat28vZ2dnVapUSb169dKpU6eKNP/58+fVs2dPOTk5ydvbW/Pnz1dERIRGjBhhauPn56dp06apd+/ecnV11cCBAyVJ69atU926dWVvby8/Pz9FRUWZjW0wGLR+/XqzMnd3d9NKc2pqqgwGg9asWaNmzZrJwcFB9erVU0xMTJFiL1++vAYPHqzQ0FBVq1ZNrVu31pAhQxQbG2tq8/bbb6t69eqKiopSUFCQhg0bpv/973+aP3/+Tcc/duyYnn/+ea1evVq2trYFtnFxcVHlypVNh5OTU5FiBwAAAHBvIum+zbKysjRq1Cjt3btXW7ZskZWVlZ544gnl5eUpMzNTHTt2VHBwsPbt26dp06Zp/PjxZv3PnTunVq1aKSQkRHv37tXGjRt14sQJde3atUjzjxo1SnFxcdqwYYM2b96s2NhY7du3L1+7uXPnqkGDBkpISNDEiRMVHx+vrl27qlu3bjp48KAmT56siRMnFnvrtiSNHTtWo0ePVkJCgsLCwtSxY0edPn262OP89ddf+vTTT9WyZUtT2a5du9SmTRuzdm3bttWuXbtuOFZeXp569eqlsWPHqm7duoW2mzVrljw9PRUSEqI5c+bo8uXLxY4bAAAAwL3DprQDuNc89dRTZufLly9XxYoVdejQIe3YsUMGg0FLly6Vg4OD6tSpo2PHjmnAgAGm9osWLVJISIhmzJhhNoavr6+Sk5MVEBBQ6Nznz5/XypUr9cEHH6h169aSpBUrVhS4lbpVq1YaPXq06bxnz55q3bq1Jk6cKEkKCAjQoUOHNGfOHEVGRhbrHgwbNsx0HxYvXqyNGzdq2bJlGjduXJH6d+/eXZ9//rn++ecfdezYUe+++66p7vjx46pUqZJZ+0qVKikzM1P//POPHB0dCxxz9uzZsrGx0fDhwwudd/jw4WrUqJE8PDy0c+dOTZgwQenp6Zo3b16B7bOzs5WdnW06v/7ZcwAAAABlHyvdt1lKSoq6d++uGjVqyNXVVX5+fpKktLQ0JSUlqX79+nJwcDC1b9KkiVn/AwcOaNu2bXJ2djYdtWvXliSzbeoFOXr0qHJycszGdHNzU2BgYL62oaGhZueJiYkKDw83KwsPD1dKSopyc3NvfuHXCAsLM/3bxsZGoaGhSkxMLHL/+fPna9++ffr888915MgRjRo1qsh9V69ebXbvYmNjFR8fr4ULFyo6OloGg6HQvqNGjVJERITq16+vQYMGKSoqSm+88YZZYn2tmTNnys3NzXT4+voWOU4AAAAAZQMr3bdZx44dVa1aNS1dulQ+Pj7Ky8tTvXr1ivyysgsXLqhjx46aPXt2vjpvb+8Si/NWnlU2GAwyGo1mZTk5OSUVksnV56lr164tDw8PtWjRQhMnTpS3t7cqV66sEydOmLU/ceKEXF1d5ejoqMcff1xNmzY11VWpUkXvvPOOTp48qapVq5rKc3NzNXr0aC1YsECpqakFxtG0aVNdvnxZqampBf7hYsKECWZ/EMjMzCTxBgAAAO4xJN230enTp5WUlKSlS5eqRYsWkqQdO3aY6gMDA/X+++8rOztb9vb2kqQ9e/aYjdGoUSOtW7dOfn5+srEp3o+vRo0asrW11Z49e0wJZkZGhpKTk/Xggw/esG9QUJDi4uLMyuLi4hQQECBra2tJUsWKFZWenm6qT0lJ0cWLF/ON9cMPP5jmu3z5suLj4zVs2LBiXctVeXl5kmRabQ4LC9PXX39t1mbz5s2m1XUXFxe5uLiY1ffq1avA58B79eqlvn37Fjr3/v37ZWVlJS8vrwLr7e3tTT9HAAAAAPcmku7bqHz58vL09NSSJUvk7e2ttLQ0vfjii6b6Hj166KWXXtLAgQP14osvKi0tTXPnzpUk07bnoUOHaunSperevbvGjRsnDw8P/frrr1qzZo3effddUwJcEBcXF/Xp00djx46Vh4eHvLy89Morr8jKyuqG26olafTo0br//vs1bdo0Pf3009q1a5cWLVqkt956y9SmVatWWrRokcLCwpSbm6vx48cX+BbwN998U7Vq1VJQUJDmz5+vs2fPql+/fje9f19//bVOnDih+++/X87Ozvrll180duxYhYeHm7bpDxo0SIsWLdK4cePUr18/bd26VWvXrtVXX31V6Lienp7y9PQ0K7O1tVXlypVNK9i7du3S7t279dBDD8nFxUW7du3SyJEj9cwzz6h8+fI3jR0AAADAvYlnum8jKysrrVmzRvHx8apXr55GjhypOXPmmOpdXV31xRdfaP/+/WrYsKFeeuklTZo0SZJMz3n7+PgoLi5Oubm5euSRRxQcHKwRI0bI3d1dVlY3/3HOmzdPYWFh6tChg9q0aaPw8HAFBQWZPUdekEaNGmnt2rVas2aN6tWrp0mTJmnq1KlmL1GLioqSr6+vWrRooR49emjMmDEqV65cvrFmzZqlWbNmqUGDBtqxY4c2bNigChUq3DR2R0dHLV26VM2bN1dQUJBGjhypxx9/XF9++aWpTfXq1fXVV19p8+bNatCggaKiovTuu++qbdu2Nx3/Ruzt7bVmzRq1bNlSdevW1fTp0zVy5EgtWbLkP40LAAAAoGwzGK9/CBd3lNWrV6tv377KyMgo9M3b/0VWVpaqVKmiqKgo9e/fv8THv1ZqaqqqV6+uhIQENWzY0KJz3YkyMzPl5uamtwK7ytG64O+AA0UV+cv7pR0CAADAPe3q7/cZGRlydXUttB3by+8wq1atUo0aNVSlShUdOHBA48ePV9euXUss4U5ISNDhw4fVpEkTZWRkaOrUqZKkTp06lcj4AAAAAID/j+3ld5jjx4/rmWeeMW2f7tKlS5G3MKelpZl9Duv6Iy0tTZI0d+5cNWjQQG3atFFWVpZiY2OLtL3b0gYNGlRo7IMGDSrt8AAAAACg2NheXoZc/XxVYW7ljee308mTJ5WZmVlgnaura6FvCb9bsL0cJYnt5QAAAKWL7eX3IBsbG/n7+5d2GLfMy8vrrk+sAQAAAOBabC8HAAAAAMBCbjnpfu+99xQeHi4fHx/9/vvvkqQFCxbo888/L7HgAAAAAAC4m91S0r148WKNGjVKjz76qM6dO6fc3FxJkru7uxYsWFCS8QEAAAAAcNe6pRep1alTRzNmzFDnzp3l4uKiAwcOqEaNGvr5558VERGhU6dOWSJW4K5W1BctAAAAALjzFfX3+1ta6f7tt98UEhKSr9ze3l5ZWVm3MiQAAAAAAGXOLSXd1atX1/79+/OVb9y4UUFBQf81JgAAAAAAyoRb+mTYqFGjNHToUP37778yGo368ccf9eGHH2rmzJl69913SzpGAAAAAADuSreUdD/77LNydHTUyy+/rIsXL6pHjx7y8fHRwoUL1a1bt5KOEQAAAACAu1Kxk+7Lly/rgw8+UNu2bdWzZ09dvHhRFy5ckJeXlyXiAwAAAADgrlXsZ7ptbGw0aNAg/fvvv5KkcuXKkXADAAAAAFCAW9pe3qRJEyUkJKhatWolHQ9Q5n3bop/KWduWdhiAJOnRfR+WdggAAABl2i0l3UOGDNHo0aP1559/qnHjxnJycjKrr1+/fokEBwAAAADA3eyWku6rL0sbPny4qcxgMMhoNMpgMCg3N7dkogMAAAAA4C52S0n3b7/9VtJxAAAAAABQ5txS0s2z3AAAAAAA3NwtJd2rVq26YX3v3r1vKRgAAAAAAMqSW0q6X3jhBbPznJwcXbx4UXZ2dipXrhxJNwAAAAAAuoXvdEvS2bNnzY4LFy4oKSlJzZs314cf8vkZAAAAAACkW0y6C1KrVi3NmjUr3yo4AAAAAAD3qhJLuiXJxsZGf/31V0kOCeRz+vRp3XfffTIYDDp37pxZXXZ2tl566SVVq1ZN9vb28vPz0/Lly2865rFjx/TMM8/I09NTjo6OCg4O1t69e031RqNRkyZNkre3txwdHdWmTRulpKSU9KUBAAAAKGNu6ZnuDRs2mJ0bjUalp6dr0aJFCg8PL5HAcGe4dOmS7OzsSjsMM/3791f9+vV17NixfHVdu3bViRMntGzZMvn7+ys9PV15eXk3HO/s2bMKDw/XQw89pG+++UYVK1ZUSkqKypcvb2rz2muv6fXXX9fKlStVvXp1TZw4UW3bttWhQ4fk4OBQ4tcIAAAAoGy4pZXuzp07mx1PPvmkJk+erPr16xdpVfFetXHjRjVv3lzu7u7y9PRUhw4ddOTIEVP9zp071bBhQzk4OCg0NFTr16+XwWDQ/v37TW1+/vlntW/fXs7OzqpUqZJ69eqlU6dOFWn+8+fPq2fPnnJycpK3t7fmz5+viIgIjRgxwtTGz89P06ZNU+/eveXq6qqBAwdKktatW6e6deuaVo+joqLMxjYYDFq/fr1Zmbu7u6KjoyVJqampMhgMWrNmjZo1ayYHBwfVq1dPMTExRb+BkhYvXqxz585pzJgx+eo2btyomJgYff3112rTpo38/PwUFhZ20z8EzZ49W76+vlqxYoWaNGmi6tWr65FHHlHNmjUlXfmj0oIFC/Tyyy+rU6dOql+/vlatWqW//vor3zUDAAAAwLVuKenOy8szO3Jzc3X8+HF98MEH8vb2LukYy4ysrCyNGjVKe/fu1ZYtW2RlZaUnnnhCeXl5yszMVMeOHRUcHKx9+/Zp2rRpGj9+vFn/c+fOqVWrVgoJCdHevXu1ceNGnThxQl27di3S/KNGjVJcXJw2bNigzZs3KzY2Vvv27cvXbu7cuWrQoIESEhI0ceJExcfHq2vXrurWrZsOHjyoyZMna+LEiaaEujjGjh2r0aNHKyEhQWFhYerYsaNOnz5dpL6HDh3S1KlTtWrVKllZ5f9Pd8OGDQoNDdVrr72mKlWqKCAgQGPGjNE///xzw3Gv9uvSpYu8vLwUEhKipUuXmup/++03HT9+XG3atDGVubm5qWnTptq1a1cRrxwAAADAveiWtpdPnTpVY8aMUbly5czK//nnH82ZM0eTJk0qkeDKmqeeesrsfPny5apYsaIOHTqkHTt2yGAwaOnSpXJwcFCdOnV07NgxDRgwwNR+0aJFCgkJ0YwZM8zG8PX1VXJysgICAgqd+/z581q5cqU++OADtW7dWpK0YsUK+fj45GvbqlUrjR492nTes2dPtW7dWhMnTpQkBQQE6NChQ5ozZ44iIyOLdQ+GDRtmug+LFy/Wxo0btWzZMo0bN+6G/bKzs9W9e3fNmTNHVatW1dGjR/O1OXr0qHbs2CEHBwd99tlnOnXqlIYMGaLTp09rxYoVhY599OhRLV68WKNGjdL//d//ac+ePRo+fLjs7OzUp08fHT9+XJJUqVIls36VKlUy1RUWc3Z2tuk8MzPzhtcIAAAAoOy5pZXuKVOm6MKFC/nKL168qClTpvznoMqqlJQUde/eXTVq1JCrq6v8/PwkSWlpaUpKSlL9+vXNng9u0qSJWf8DBw5o27ZtcnZ2Nh21a9eWJLNt6gU5evSocnJyzMZ0c3NTYGBgvrahoaFm54mJifm2aIeHhyslJUW5ubk3v/BrhIWFmf5tY2Oj0NBQJSYm3rTfhAkTFBQUpGeeeabQNnl5eTIYDFq9erWaNGmiRx99VPPmzdPKlSv1zz//KDY21uzerV692tSvUaNGmjFjhkJCQjRw4EANGDBAb7/9drGu7XozZ86Um5ub6fD19f1P4wEAAAC4+9zSSrfRaJTBYMhXfuDAAXl4ePznoMqqjh07qlq1alq6dKl8fHyUl5enevXq6dKlS0Xqf+HCBXXs2FGzZ8/OV1eS2/qdnJyK3cdgMMhoNJqV5eTklFRI2rp1qw4ePKhPPvlEkkxzVahQQS+99JKmTJkib29vValSRW5ubqZ+QUFBMhqN+vPPPxUaGmr2fPzVlWtvb2/VqVPHbL6goCCtW7dOklS5cmVJ0okTJ8zu84kTJ9SwYcNCY54wYYJGjRplOs/MzCTxBgAAAO4xxUq6y5cvL4PBIIPBoICAALPEOzc3VxcuXNCgQYNKPMiy4PTp00pKStLSpUvVokULSdKOHTtM9YGBgXr//feVnZ0te3t7SdKePXvMxmjUqJHWrVsnPz8/2dgU7+8lNWrUkK2trfbs2aOqVatKkjIyMpScnKwHH3zwhn2DgoIUFxdnVhYXF6eAgABZW1tLkipWrKj09HRTfUpKii5evJhvrB9++ME03+XLlxUfH69hw4bdNP5169aZPZu9Z88e9evXT7GxsaYXnoWHh+vjjz/WhQsX5OzsLElKTk6WlZWV7rvvPjk6Osrf3z/f2OHh4UpKSjIrS05OVrVq1SRJ1atXV+XKlbVlyxZTkp2Zmandu3dr8ODBhcZsb29v+lkCAAAAuDcVK3NbsGCBjEaj+vXrpylTppitKNrZ2ZneFo38ypcvL09PTy1ZskTe3t5KS0vTiy++aKrv0aOHXnrpJQ0cOFAvvvii0tLSNHfuXEky/XFj6NChWrp0qbp3765x48bJw8NDv/76q9asWaN3333XlAAXxMXFRX369NHYsWPl4eEhLy8vvfLKK7Kysipw18K1Ro8erfvvv1/Tpk3T008/rV27dmnRokV66623TG1atWqlRYsWKSwsTLm5uRo/frxsbW3zjfXmm2+qVq1aCgoK0vz583X27Fn169fvpvfvamJ91dU3tgcFBcnd3d10D6dNm6a+fftqypQpOnXqlMaOHat+/frJ0dGx0LFHjhypZs2aacaMGeratat+/PFHLVmyREuWLJF05f6PGDFCr776qmrVqmX6ZJiPj486d+5809gBAAAA3LuKlXT36dNH0pWVv2bNmhWYVKFgVlZWWrNmjYYPH6569eopMDBQr7/+uiIiIiRJrq6u+uKLLzR48GA1bNhQwcHBmjRpknr06GF6ztvHx0dxcXEaP368HnnkEWVnZ6tatWpq165dgW/zvt68efM0aNAgdejQQa6urho3bpz++OOPm35nulGjRlq7dq0mTZqkadOmydvbW1OnTjV7iVpUVJT69u2rFi1ayMfHRwsXLlR8fHy+sWbNmqVZs2Zp//798vf314YNG1ShQoWi38gbcHZ21ubNm/X8888rNDRUnp6e6tq1q1599dUb9rv//vv12WefacKECZo6daqqV6+uBQsWqGfPnqY248aNU1ZWlgYOHKhz586pefPm2rhxI9/oBgAAAHBDBuP1D+IW07///pvvmWRXV9f/FBSuWL16tfr27auMjIwbrtTeqqysLFWpUkVRUVHq379/iY9/rdTUVFWvXl0JCQk3fA66LMvMzJSbm5s+rv+UylnzByvcGR7d92FphwAAAHBXuvr7fUZGxg1z4Ft6kdrFixc1btw4rV27tsBvLBf3jda4YtWqVapRo4aqVKmiAwcOaPz48eratWuJJdwJCQk6fPiwmjRpooyMDE2dOlWS1KlTpxIZHwAAAABg7pY+GTZ27Fht3bpVixcvlr29vd59911NmTJFPj4+WrVqVUnHeM84fvy4nnnmGQUFBWnkyJHq0qWL6bnim0lLSzP7HNb1R1pamiRp7ty5atCggdq0aaOsrCzFxsaW2Pbu/2LQoEGFxs7L+QAAAADcrW5pe3nVqlW1atUqRUREyNXVVfv27ZO/v7/ee+89ffjhh/r6668tEStu4PLly0pNTS20/lbeeH47nTx5UpmZmQXWubq6ysvL6zZHVPLYXo47EdvLAQAAbo1Ft5efOXNGNWrUkHQlITpz5owkqXnz5jf8hBIsx8bGpsDPYd0tvLy8ykRiDQAAAADXuqXt5TVq1NBvv/0mSapdu7bWrl0rSfriiy9Mn28CAAAAAOBed0tJd9++fXXgwAFJ0osvvqg333xTDg4OGjlypMaOHVuiAQIAAAAAcLe6pe3lI0eONP27TZs2Onz4sOLj4+Xv76/69euXWHAAAAAAANzNSuQ73Q4ODiUVD1BmFfVFCwAAAADufEX9/f6Wtpfn5uZq2rRpqlKlipydnXX06FFJ0sSJE7Vs2bJbixgAAAAAgDLmlpLu6dOnKzo6Wq+99prs7OxM5fXq1dO7775bYsEBAAAAAHA3u6Wke9WqVVqyZIl69uwpa2trU3mDBg10+PDhEgsOAAAAAIC72S0l3ceOHSvwm9B5eXnKycn5z0EBAAAAAFAW3FLSXadOHcXGxuYr/+STTxQSEvKfgwIAAAAAoCy4pU+GTZo0SX369NGxY8eUl5enTz/9VElJSVq1apW+/PLLko4RAAAAAIC7UrE+GXb06FFVr15dBoNBsbGxmjp1qg4cOKALFy6oUaNGmjRpkh555BFLxgvcta5+UmDLQ53lbGNb2uEAxdLk27WlHQIAAMAdpaifDCvWSnetWrWUnp4uLy8vtWjRQh4eHjp48KAqVar0nwMGAAAAAKCsKdYz3dcvin/zzTfKysoq0YAAAAAAACgrbulFalcVY2c6AAAAAAD3nGIl3QaDQQaDIV8ZAAAAAADIr1jPdBuNRkVGRsre3l6S9O+//2rQoEFycnIya/fpp5+WXIQAAAAAANylipV09+nTx+z8mWeeKdFgAAAAAAAoS4qVdK9YscJScQAAAAAAUOb8pxepAQAAAACAwpF0464SHR2t+vXry8HBQV5eXho6dKip7t9//1VkZKSCg4NlY2Ojzp07F2nMiIgI00sCrz0ee+wxU5vIyMh89e3atSvpywMAAABQxhRreznuPZcuXZKdnV1phyFJmjdvnqKiojRnzhw1bdpUWVlZSk1NNdXn5ubK0dFRw4cP17p164o87qeffqpLly6Zzk+fPq0GDRqoS5cuZu3atWtn9ojF1RcKAgAAAEBhWOm+jTZu3KjmzZvL3d1dnp6e6tChg44cOWKq37lzpxo2bCgHBweFhoZq/fr1MhgM2r9/v6nNzz//rPbt28vZ2VmVKlVSr169dOrUqSLNf/78efXs2VNOTk7y9vbW/PnzFRERoREjRpja+Pn5adq0aerdu7dcXV01cOBASdK6detUt25d2dvby8/PT1FRUWZjGwwGrV+/3qzM3d1d0dHRkqTU1FQZDAatWbNGzZo1k4ODg+rVq6eYmJgixX727Fm9/PLLWrVqlXr06KGaNWuqfv36evzxx01tnJyctHjxYg0YMECVK1cu0riS5OHhocqVK5uOzZs3q1y5cvmSbnt7e7N25cuXL/IcAAAAAO5NJN23UVZWlkaNGqW9e/dqy5YtsrKy0hNPPKG8vDxlZmaqY8eOCg4O1r59+zRt2jSNHz/erP+5c+fUqlUrhYSEaO/evdq4caNOnDihrl27Fmn+UaNGKS4uThs2bNDmzZsVGxurffv25Ws3d+5cNWjQQAkJCZo4caLi4+PVtWtXdevWTQcPHtTkyZM1ceJEU0JdHGPHjtXo0aOVkJCgsLAwdezYUadPn75pv82bNysvL0/Hjh1TUFCQ7rvvPnXt2lV//PFHsWO4mWXLlqlbt275PoW3fft2eXl5KTAwUIMHD75p3NnZ2crMzDQ7AAAAANxb2F5+Gz311FNm58uXL1fFihV16NAh7dixQwaDQUuXLpWDg4Pq1KmjY8eOacCAAab2ixYtUkhIiGbMmGE2hq+vr5KTkxUQEFDo3OfPn9fKlSv1wQcfqHXr1pKuvI3ex8cnX9tWrVpp9OjRpvOePXuqdevWmjhxoiQpICBAhw4d0pw5cxQZGVmsezBs2DDTfVi8eLE2btyoZcuWady4cTfsd/ToUeXl5WnGjBlauHCh3Nzc9PLLL+vhhx/WTz/9VGJb4H/88Uf9/PPPWrZsmVl5u3bt9OSTT6p69eo6cuSI/u///k/t27fXrl27ZG1tXeBYM2fO1JQpU0okLgAAAAB3J1a6b6OUlBR1795dNWrUkKurq/z8/CRJaWlpSkpKMr0g7KomTZqY9T9w4IC2bdsmZ2dn01G7dm1JMtumXpCjR48qJyfHbEw3NzcFBgbmaxsaGmp2npiYqPDwcLOy8PBwpaSkKDc39+YXfo2wsDDTv21sbBQaGqrExMSb9svLy1NOTo5ef/11tW3bVg888IA+/PBDpaSkaNu2bUWaOy0tzezeXfvHi6uWLVum4ODgfPe+W7duevzxxxUcHKzOnTvryy+/1J49e7R9+/ZC55swYYIyMjJMhyVW5QEAAADc2Vjpvo06duyoatWqaenSpfLx8VFeXp7q1atn9hKvG7lw4YI6duyo2bNn56vz9vYusTiv31ZdFAaDQUaj0awsJyenpEIyXV+dOnVMZRUrVlSFChWUlpZWpDF8fHzMno/38PAwq8/KytKaNWs0derUm45Vo0YNVahQQb/++qtp58D17O3tedkaAAAAcI9jpfs2OX36tJKSkvTyyy+rdevWCgoK0tmzZ031gYGBOnjwoLKzs01le/bsMRujUaNG+uWXX+Tn5yd/f3+z42aJco0aNWRra2s2ZkZGhpKTk28ae1BQkOLi4szK4uLiFBAQYNpaXbFiRaWnp5vqU1JSdPHixXxj/fDDD6Z/X758WfHx8QoKCrppDFdX2pOSkkxlZ86c0alTp1StWrWb9peurKxfe8+uT7o//vhjZWdn65lnnrnpWH/++adOnz5don/sAAAAAFD2kHTfJuXLl5enp6eWLFmiX3/9VVu3btWoUaNM9T169FBeXp4GDhyoxMREbdq0SXPnzpV0ZRVZkoYOHaozZ86oe/fu2rNnj44cOaJNmzapb9++N93m7eLioj59+mjs2LHatm2bfvnlF/Xv319WVlam8QszevRobdmyRdOmTVNycrJWrlypRYsWacyYMaY2rVq10qJFi5SQkKC9e/dq0KBBsrW1zTfWm2++qc8++0yHDx/W0KFDdfbsWfXr1++m9y8gIECdOnXSCy+8oJ07d+rnn39Wnz59VLt2bT300EOmdocOHdL+/ft15swZZWRkaP/+/War2zeybNkyde7cWZ6enmblFy5c0NixY/XDDz8oNTVVW7ZsUadOneTv76+2bdsWaWwAAAAA9yaS7tvEyspKa9asUXx8vOrVq6eRI0dqzpw5pnpXV1d98cUX2r9/vxo2bKiXXnpJkyZNkiTTc94+Pj6Ki4tTbm6uHnnkEQUHB2vEiBFyd3eXldXNf5Tz5s1TWFiYOnTooDZt2ig8PFxBQUFmz5EXpFGjRlq7dq3WrFmjevXqadKkSZo6darZS9SioqLk6+urFi1aqEePHhozZozKlSuXb6xZs2Zp1qxZatCggXbs2KENGzaoQoUKRbmFWrVqlZo2barHHntMLVu2lK2trTZu3GiW3D/66KMKCQnRF198oe3btyskJEQhISE3HTspKUk7duxQ//7989VZW1vrp59+0uOPP66AgAD1799fjRs3VmxsLNvHAQAAANyQwXj9g7i4Y6xevVp9+/ZVRkaGHB0dS3z8rKwsValSRVFRUQUmmyUpNTVV1atXV0JCgho2bGjRue5UmZmZcnNz05aHOsvZJv8uAOBO1uTbtaUdAgAAwB3l6u/3GRkZcnV1LbQdL1K7g6xatUo1atRQlSpVdODAAY0fP15du3YtsYQ7ISFBhw8fVpMmTZSRkWF6YVinTp1KZHwAAAAAgDm2l99Bjh8/rmeeeUZBQUEaOXKkunTpoiVLlhSp7/Wfw7r+uPqG77lz56pBgwZq06aNsrKyFBsbW+Tt3ZY0aNCgQmMfNGhQaYcHAAAAALeE7eVlxOXLl5WamlpovZ+fn2xs7tyNDSdPnlRmZmaBda6urvLy8rrNEZU8tpfjbsb2cgAAAHNsL7/HXP0c1t3Ky8urTCTWAAAAAHAttpcDAAAAAGAhJN0AAAAAAFgISTcAAAAAABbCM93AbRa6fuUNX7QAAAAAoOxgpRsAAAAAAAsh6QYAAAAAwEJIugEAAAAAsBCSbgAAAAAALISkGwAAAAAAC+Ht5cBtlvxcbznb2ZZ2GLjD1V75cWmHAAAAgBLASjcAAAAAABZC0g0AAAAAgIWQdAMAAAAAYCEk3QAAAAAAWAhJNwAAAAAAFkLSDQAAAACAhZB0AwAAAABgISTdAAAAAABYCEk3ypzo6GgZDIYCj5MnT0qStm/fXmD98ePHSzl6AAAAAGWJTWkHgLLj0qVLsrOzK+0w9PTTT6tdu3ZmZZGRkfr333/l5eVlVp6UlCRXV1fT+fX114qIiFBkZKQiIyNLNF4AAAAAZRcr3XeojRs3qnnz5nJ3d5enp6c6dOigI0eOmOp37typhg0bysHBQaGhoVq/fr0MBoP2799vavPzzz+rffv2cnZ2VqVKldSrVy+dOnWqSPOfP39ePXv2lJOTk7y9vTV//nxFRERoxIgRpjZ+fn6aNm2aevfuLVdXVw0cOFCStG7dOtWtW1f29vby8/NTVFSU2dgGg0Hr1683K3N3d1d0dLQkKTU1VQaDQWvWrFGzZs3k4OCgevXqKSYmpkixOzo6qnLlyqbD2tpaW7duVf/+/fO19fLyMmtrZcX/JAAAAACUHDKMO1RWVpZGjRqlvXv3asuWLbKystITTzyhvLw8ZWZmqmPHjgoODta+ffs0bdo0jR8/3qz/uXPn1KpVK4WEhGjv3r3auHGjTpw4oa5duxZp/lGjRikuLk4bNmzQ5s2bFRsbq3379uVrN3fuXDVo0EAJCQmaOHGi4uPj1bVrV3Xr1k0HDx7U5MmTNXHiRFNCXRxjx47V6NGjlZCQoLCwMHXs2FGnT58u9jirVq1SuXLl9L///S9fXcOGDeXt7a2HH35YcXFxxR4bAAAAAG6E7eV3qKeeesrsfPny5apYsaIOHTqkHTt2yGAwaOnSpXJwcFCdOnV07NgxDRgwwNR+0aJFCgkJ0YwZM8zG8PX1VXJysgICAgqd+/z581q5cqU++OADtW7dWpK0YsUK+fj45GvbqlUrjR492nTes2dPtW7dWhMnTpQkBQQE6NChQ5ozZ06xt2UPGzbMdB8WL16sjRs3atmyZRo3blyxxlm2bJl69OghR0dHU5m3t7fefvtthYaGKjs7W++++64iIiK0e/duNWrUqFjjFyY7O1vZ2dmm88zMzBIZFwAAAMDdg5XuO1RKSoq6d++uGjVqyNXVVX5+fpKktLQ0JSUlqX79+nJwcDC1b9KkiVn/AwcOaNu2bXJ2djYdtWvXliSzbeoFOXr0qHJycszGdHNzU2BgYL62oaGhZueJiYkKDw83KwsPD1dKSopyc3NvfuHXCAsLM/3bxsZGoaGhSkxMLNYYu3btUmJiYr6t5YGBgXruuefUuHFjNWvWTMuXL1ezZs00f/58U5sZM2aY3b/Y2FgNGjTIrCwtLa3QuWfOnCk3NzfT4evrW6zYAQAAANz9WOm+Q3Xs2FHVqlXT0qVL5ePjo7y8PNWrV0+XLl0qUv8LFy6oY8eOmj17dr46b2/vEovTycmp2H0MBoOMRqNZWU5OTkmFZObdd99Vw4YN1bhx45u2bdKkiXbs2GE6HzRokNl2/J49e+qpp57Sk08+aSoraPX/qgkTJmjUqFGm88zMTBJvAAAA4B5D0n0HOn36tJKSkrR06VK1aNFCksySwcDAQL3//vvKzs6Wvb29JGnPnj1mYzRq1Ejr1q2Tn5+fbGyK92OuUaOGbG1ttWfPHlWtWlWSlJGRoeTkZD344IM37BsUFJTv2ei4uDgFBATI2tpaklSxYkWlp6eb6lNSUnTx4sV8Y/3www+m+S5fvqz4+HgNGzasyNdx4cIFrV27VjNnzixS+/3795v9QcLDw0MeHh6mc0dHR3l5ecnf379I49nb25t+PgAAAADuTWwvvwOVL19enp6eWrJkiX799Vdt3brVbMW0R48eysvL08CBA5WYmKhNmzZp7ty5kq6sIkvS0KFDdebMGXXv3l179uzRkSNHtGnTJvXt2/em27xdXFzUp08fjR07Vtu2bdMvv/yi/v37y8rKyjR+YUaPHq0tW7Zo2rRpSk5O1sqVK7Vo0SKNGTPG1KZVq1ZatGiREhIStHfvXg0aNEi2trb5xnrzzTf12Wef6fDhwxo6dKjOnj2rfv36Ffk+fvTRR7p8+bKeeeaZfHULFizQ559/rl9//VU///yzRowYoa1bt2ro0KFFHh8AAAAAboak+w5kZWWlNWvWKD4+XvXq1dPIkSM1Z84cU72rq6u++OIL7d+/Xw0bNtRLL72kSZMmSZLpOW8fHx/FxcUpNzdXjzzyiIKDgzVixAi5u7sX6bNY8+bNU1hYmDp06KA2bdooPDxcQUFBZs+RF6RRo0Zau3at1qxZo3r16mnSpEmaOnWq2UvUoqKi5OvrqxYtWqhHjx4aM2aMypUrl2+sWbNmadasWWrQoIF27NihDRs2qEKFCkW5hZKuvEDtySeflLu7e766S5cuafTo0QoODlbLli114MABfffdd6YXxwEAAABASTAYr3+4Fnel1atXq2/fvsrIyDB7S3dJycrKUpUqVRQVFVXg965LUmpqqqpXr66EhAQ1bNjQonPdTpmZmXJzc9Oebp3kbJd/ZR+4Vu2VH5d2CAAAALiBq7/fZ2RkyNXVtdB2PNN9l1q1apVq1KihKlWq6MCBAxo/fry6du1aYgl3QkKCDh8+rCZNmigjI0NTp06VJHXq1KlExgcAAACAewHby+9Sx48f1zPPPKOgoCCNHDlSXbp00ZIlS4rUNy0tzeyzV9cfVz+DNXfuXDVo0EBt2rRRVlaWYmNji7W921Ku/2zXtcegQYNKOzwAAAAAMGF7+T3o8uXLSk1NLbT+Vt54fjudPHlSmZmZBda5urrKy8vrNkdUNGwvR3GwvRwAAODOxvZyFMrGxqbIn726E3l5ed2xiTUAAAAAXIvt5QAAAAAAWAhJNwAAAAAAFkLSDQAAAACAhfBMN3CbBbyz6oYvWgAAAABQdrDSDQAAAACAhZB0AwAAAABgISTdAAAAAABYCEk3AAAAAAAWQtINAAAAAICFkHQDAAAAAGAhfDIMuM1+m/ycXOztSjsMQJJUY+bK0g4BAACgTGOlGwAAAAAACyHpBgAAAADAQki6AQAAAACwEJJuAAAAAAAshKQbAAAAAAALIekGAAAAAMBCSLoBAAAAALAQkm5YTGRkpDp37lzaYdyS6Ohoubu7l3YYAAAAAO5yJN0AAAAAAFgISTfuWEajUZcvXy7tMAAAAADglpF03wPOnz+vnj17ysnJSd7e3po/f74iIiI0YsQISVJ2drbGjBmjKlWqyMnJSU2bNtX27dtN/a9utd60aZOCgoLk7Oysdu3aKT093dQmNzdXo0aNkru7uzw9PTVu3DgZjUazOPLy8jRz5kxVr15djo6OatCggT755BNT/fbt22UwGPTNN9+ocePGsre3144dO254bZMnT1bDhg21fPlyVa1aVc7OzhoyZIhyc3P12muvqXLlyvLy8tL06dPN+s2bN0/BwcFycnKSr6+vhgwZogsXLtxwrs8//1yNGjWSg4ODatSooSlTpvBHAQAAAAA3RNJ9Dxg1apTi4uK0YcMGbd68WbGxsdq3b5+pftiwYdq1a5fWrFmjn376SV26dFG7du2UkpJianPx4kXNnTtX7733nr7//nulpaVpzJgxpvqoqChFR0dr+fLl2rFjh86cOaPPPvvMLI6ZM2dq1apVevvtt/XLL79o5MiReuaZZxQTE2PW7sUXX9SsWbOUmJio+vXr3/T6jhw5om+++UYbN27Uhx9+qGXLlumxxx7Tn3/+qZiYGM2ePVsvv/yydu/ebepjZWWl119/Xb/88otWrlyprVu3aty4cYXOERsbq969e+uFF17QoUOH9M477yg6OjpfMn+t7OxsZWZmmh0AAAAA7i0G4/XLkShTzp8/L09PT33wwQf63//+J0nKyMiQj4+PBgwYoFGjRqlGjRpKS0uTj4+PqV+bNm3UpEkTzZgxQ9HR0erbt69+/fVX1axZU5L01ltvaerUqTp+/LgkycfHRyNHjtTYsWMlSZcvX1b16tXVuHFjrV+/XtnZ2fLw8NB3332nsLAw0zzPPvusLl68qA8++EDbt2/XQw89pPXr16tTp05Fur7Jkydrzpw5On78uFxcXCRJ7dq1U1JSko4cOSIrqyt/V6pdu7YiIyP14osvFjjOJ598okGDBunUqVOSrqzujxgxQufOnTPdj9atW2vChAmmPu+//77GjRunv/76q9DYpkyZkq98/8hucrG3K9L1AZZWY+bK0g4BAADgrpSZmSk3NzdlZGTI1dW10HY2tzEmlIKjR48qJydHTZo0MZW5ubkpMDBQknTw4EHl5uYqICDArF92drY8PT1N5+XKlTMl3JLk7e2tkydPSrqSxKenp6tp06amehsbG4WGhpq2mP/666+6ePGiHn74YbN5Ll26pJCQELOy0NDQYl2jn5+fKeGWpEqVKsna2tqUcF8tuxqvJH333XeaOXOmDh8+rMzMTF2+fFn//vuvLl68qHLlyuWb48CBA4qLizNb2c7Nzb1hnwkTJmjUqFGm88zMTPn6+hbr2gAAAADc3Ui673EXLlyQtbW14uPjZW1tbVbn7Oxs+retra1ZncFgyPfM9s3mkaSvvvpKVapUMauzt7c3O3dyciryuIXFVlBZXl6eJCk1NVUdOnTQ4MGDNX36dHl4eGjHjh3q37+/Ll26VGACfeHCBU2ZMkVPPvlkvjoHB4cC47K3t893bQAAAADuLSTdZVyNGjVka2urPXv2qGrVqpKurEwnJyfrwQcfVEhIiHJzc3Xy5Em1aNHiluZwc3OTt7e3du/erQcffFDSle3l8fHxatSokSSpTp06sre3V1pamlq2bFkyF3eL4uPjlZeXp6ioKNNq+Nq1a2/Yp1GjRkpKSpK/v//tCBEAAABAGUHSXca5uLioT58+Gjt2rDw8POTl5aVXXnlFVlZWMhgMCggIUM+ePdW7d29FRUUpJCREf//9t7Zs2aL69evrscceK9I8L7zwgmbNmqVatWqpdu3amjdvnul56KtxjBkzRiNHjlReXp6aN2+ujIwMxcXFydXVVX369LHQHcjP399fOTk5euONN9SxY0fFxcXp7bffvmGfSZMmqUOHDqpatar+97//ycrKSgcOHNDPP/+sV1999TZFDgAAAOBuw9vL7wHz5s1TWFiYOnTooDZt2ig8PFxBQUGmbdErVqxQ7969NXr0aAUGBqpz585mK+NFMXr0aPXq1Ut9+vRRWFiYXFxc9MQTT5i1mTZtmiZOnKiZM2cqKChI7dq101dffaXq1auX6PXeTIMGDTRv3jzNnj1b9erV0+rVqzVz5swb9mnbtq2+/PJLffvtt7r//vv1wAMPaP78+apWrdptihoAAADA3Yi3l9+DsrKyVKVKFUVFRal///6lHc494+rbDXl7Oe4kvL0cAADg1vD2cpgkJCTo8OHDatKkiTIyMjR16lRJKvJnuQAAAAAAt4bt5feIuXPnqkGDBmrTpo2ysrIUGxurChUqlHZYN1W3bl05OzsXeKxevbq0wwMAAACAG2Kl+x4QEhKi+Pj40g7jlnz99dfKyckpsK5SpUq3ORoAAAAAKB6SbtzReFEZAAAAgLsZ28sBAAAAALAQkm4AAAAAACyEpBsAAAAAAAvhmW7gNqs++Z0bfscPAAAAQNnBSjcAAAAAABZC0g0AAAAAgIWQdAMAAAAAYCEk3QAAAAAAWAhJNwAAAAAAFkLSDQAAAACAhfDJMOA2+3Px/8nFwb60w0AZ5/tCVGmHAAAAALHSDQAAAACAxZB0AwAAAABgISTdAAAAAABYCEk3AAAAAAAWQtINAAAAAICFkHQDAAAAAGAhJN0AAAAAAFjIHZt0G41GDRw4UB4eHjIYDHJ3d9eIESNKOyyUosmTJ6thw4alHQYAAAAAFJlNaQdQmI0bNyo6Olrbt29XjRo1ZGVlJUdHx/80psFg0GeffabOnTuXTJC4rcaMGaPnn3++tMMAAAAAgCK7Y5PuI0eOyNvbW82aNStS+0uXLsnOzs7CUd257oXrd3Z2lrOzc2mHAQAAAABFdkduL4+MjNTzzz+vtLQ0GQwG+fn5KSIiwmx7uZ+fn6ZNm6bevXvL1dVVAwcO1KVLlzRs2DB5e3vLwcFB1ar9v/buPCqqK3sf/lOgDFIFJYMMyiARCaI4gQaNQhwC0tpITDBKKyS2+DUimmhi06sRlSSgASNoYkdNgCgRJbaKiiNtGURUVHBEJkFMx+EnEhQnFO77h8v7WgpYDAUoz2etWqHuOXfXPpcTV23OqVvWiIiIEPsDgI+PjxhTFTt27ICLiwt0dHRgbGwMHx8fsW39+vVwdnaGTCaDmZkZJk+ejBs3bojt5eXl8PPzg4mJCXR1dWFnZ4e4uDix/cqVK/D19YVcLoehoSG8vb1RUlKi8jUaP348vvrqK1hYWMDe3l6lmFlZWRg9ejSMjY1hYGAANzc3nDp1SmwXBAGLFi2ClZUVtLW1YWFhgeDgYKUxTZ06FZ07d0anTp0wZswYFBQUiO3x8fGQy+XYu3cvHBwcIJVK4enpiatXr6o0LoVCgUGDBkFPTw9yuRxDhw7F5cuXAby4vfzx48cIDg6GXC6HkZERFixYAH9/f6WdDO7u7ggODsYXX3wBQ0NDmJmZYdGiRWJ7SUkJJBIJcnJyxGN//vknJBIJFAqFmJNEIsGuXbvg5OQEHR0dvPXWWzh37pxKYyIiIiIiovarTRbdMTExWLJkCbp164arV68iKyur1n5RUVHo27cvsrOzERoaitjYWKSkpGDz5s3Iy8tDYmKiWFw/jREXF1dvzGft2rULPj4+8PLyQnZ2NtLS0jBo0CCx/dGjRwgPD8fp06exbds2lJSUICAgQGwPDQ3FhQsXsHv3buTm5mL16tUwNjYWz/Xw8IBMJkN6ejoyMjLEArWqqkql65SWloa8vDzs378fO3fuVCnmnTt34O/vj8OHD+Po0aOws7ODl5cX7ty5AwDYsmULvv32W/zwww8oKCjAtm3b0KdPH/E1AwICcOLECaSkpCAzMxOCIMDLywuPHj0S+9y7dw9RUVFYv349fvvtN5SWlmL+/PkvHc/jx48xfvx4uLm54cyZM8jMzERgYCAkEkmt/ZcuXYrExETExcUhIyMDt2/fxrZt217ol5CQAD09PRw7dgzLli3DkiVLsH//fpWu8bM+//xzREdHIysrCyYmJhg3bpzSuJ/38OFD3L59W+lBRERERETtS5vcXm5gYACZTAZNTU2YmZnV2W/EiBGYN2+e+Ly0tBR2dnZ4++23IZFIYG1tLbaZmJgAAORyeb0xn/XVV1/hww8/xOLFi8Vjffv2FX/++OOPxZ9tbW0RGxsLFxcXVFZWQiqVorS0FP3794ezszMAKK2ub9q0CTU1NVi3bp1YVMbFxUEul0OhUODdd999aX56enpYt26duK18w4YNL405YsQIpRhr1qyBXC7HoUOHMHbsWJSWlsLMzAyjRo1Cx44dYWVlJf6hoaCgACkpKcjIyBC3/ScmJsLS0hLbtm3DBx98AODJHxT+/e9/44033gAABAUFYcmSJS8dz+3bt1FRUYGxY8eK5zo4ONTZf+XKlQgJCRF3H6xatQqpqakv9HNyckJYWBgAwM7ODqtWrUJaWhpGjx790pyeFRYWJp6TkJCAbt26YevWrfD19a21f0REhNLcISIiIiKi9qdNrnSr6mkx+1RAQABycnJgb2+P4OBg7Nu3r0nxc3JyMHLkyDrbT548iXHjxsHKygoymQxubm4AnhT/ADBz5kwkJSWhX79++OKLL3DkyBHx3NOnT6OwsBAymUz8rLKhoSEePHiAoqIilfLr06eP0ue4VYl5/fp1TJ8+HXZ2djAwMIC+vj4qKyvFnD/44APcv38ftra2mD59OrZu3YrHjx8DAHJzc9GhQwcMHjxYfE0jIyPY29sjNzdXPNapUyexaAYAc3NzpW33dTE0NERAQAA8PDwwbtw4xMTE1LktvaKiAtevX1faeaCpqYmBAwe+0NfJyUnpuar5PM/V1VUp1+fH/byQkBBUVFSIjytXrjT4NYmIiIiI6NX2Shfdenp6Ss8HDBiA4uJihIeH4/79+/D19cX777/f6Pj13S397t278PDwgL6+PhITE5GVlYWtW7cCgLiVe8yYMbh8+TI+/fRT/PHHHxg5cqS4zbqyshIDBw5ETk6O0iM/Px+TJ09WKb/nx69KTH9/f+Tk5CAmJgZHjhxBTk4OjIyMxJwtLS2Rl5eH77//Hrq6uvjkk08wfPjwerdRP69jx45KzyUSCQRBUOncuLg4ZGZmYsiQIdi0aRN69uyJo0ePqvzaquZTU1MDANDQePK/wLP5NWSs9dHW1oa+vr7Sg4iIiIiI2pdXuuiujb6+PiZOnIi1a9di06ZN2LJlC27dugXgSfFVXV2tciwnJyekpaXV2nbx4kWUlZUhMjISw4YNw5tvvlnr6qmJiQn8/f2xYcMGrFixAmvWrAHw5A8EBQUF6NKlC3r06KH0MDAwaMTIVYuZkZGB4OBgeHl5wdHREdra2rh586ZSHF1dXYwbNw6xsbFQKBTIzMzE2bNn4eDggMePH+PYsWNi37KyMuTl5aFXr16Nyrk2/fv3R0hICI4cOYLevXvjl19+eaGPgYEBTE1NlT6bX11drXRTOFU8/djBsyvqz95U7VnPFv/l5eXIz8+vd/s7ERERERHRa1V0L1++HBs3bsTFixeRn5+P5ORkmJmZQS6XA3jymeq0tDRcu3YN5eXlL40XFhaGjRs3IiwsDLm5uTh79iyWLl0KALCysoKWlhZWrlyJS5cuISUlBeHh4UrnL1y4ENu3b0dhYSHOnz+PnTt3ikWan58fjI2N4e3tjfT0dBQXF0OhUCA4OBi///57o8avSkw7OzusX78eubm5OHbsGPz8/JRW9OPj4/Hjjz/i3LlzuHTpEjZs2ABdXV1YW1vDzs4O3t7emD59Og4fPozTp0/jb3/7G7p27Qpvb+9G5fys4uJihISEIDMzE5cvX8a+fftQUFBQZ2E7e/ZsREREYPv27cjLy8OcOXNQXl5e543XaqOrq4u33noLkZGRyM3NxaFDh/Cvf/2r1r5LlixBWloazp07h4CAABgbG/M734mIiIiIqF6vVdEtk8mwbNkyODs7w8XFBSUlJUhNTRW3EEdHR2P//v2wtLRE//79XxrP3d0dycnJSElJQb9+/TBixAgcP34cwJMV0vj4eCQnJ6NXr16IjIxEVFSU0vlaWloICQmBk5MThg8fDk1NTSQlJQF48rnn3377DVZWVnjvvffg4OCAadOm4cGDB43ehqxKzB9//BHl5eUYMGAApkyZguDgYHTp0kWMIZfLsXbtWgwdOhROTk44cOAAduzYASMjIwBPtn8PHDgQY8eOhaurKwRBQGpq6gtbuBub/8WLFzFhwgT07NkTgYGBmDVrFmbMmFFr/wULFmDSpEmYOnUqXF1dIZVK4eHhAR0dnQa97k8//YTHjx9j4MCBmDt3Lr788sta+0VGRmLOnDkYOHAgrl27hh07drz2341ORERERERNIxFU/bAtURtXU1MDBwcH+Pr6vrDroCkUCgXeeecdlJeXi7smGuP27dswMDDA+chZkOloN1t+RLWxnBPd2ikQERERvdaevr+vqKiod+G0TX5lGJEqnm5Bd3Nzw8OHD7Fq1SoUFxerfCM6IiIiIiIidXuttpc3lKOjo/jVWs8/EhMTWzW3uvKSSqVIT09v1dyaojnHpaGhgfj4eLi4uGDo0KE4e/YsDhw4wJubERERERFRm9GuV7pTU1Pr/HooU1PTFs5GWV130AaArl27tlwizaw5x2VpaYmMjIwmZvRy7u7uKn/lGRERERER0bPaddFtbW3d2inUqUePHq2dglq8ruMiIiIiIiKqTbveXk5ERERERESkTiy6iYiIiIiIiNSkXW8vJ2oN3WZ+3ejvYiciIiIiolcLV7qJiIiIiIiI1IRFNxEREREREZGasOgmIiIiIiIiUhMW3URERERERERqwqKbiIiIiIiISE1YdBMRERERERGpCYtuIiIiIiIiIjVh0U1ERERERESkJiy6iYiIiIiIiNSERTcRERERERGRmrDoJiIiIiIiIlITFt1EREREREREasKim4iIiIiIiEhNWHQTERERERERqUmrFt2CICAwMBCGhoaQSCSQy+WYO3dua6ZERERERERE1Gw6tOaL79mzB/Hx8VAoFLC1tYWGhgZ0dXWbFFMikWDr1q0YP3588yRJ9Bx3d3f069cPK1asaO1UiIiIiIiojWvVoruoqAjm5uYYMmSISv2rqqqgpaWl5qzarvY+/tbG609ERERERA3VatvLAwICMHv2bJSWlkIikcDGxgbu7u5K28ttbGwQHh6OqVOnQl9fH4GBgaiqqkJQUBDMzc2ho6MDa2trREREiP0BwMfHR4ypih07dsDFxQU6OjowNjaGj4+P2LZ+/Xo4OztDJpPBzMwMkydPxo0bN8T28vJy+Pn5wcTEBLq6urCzs0NcXJzYfuXKFfj6+kIul8PQ0BDe3t4oKSlR+RqNHz8eX331FSwsLGBvb69SzKysLIwePRrGxsYwMDCAm5sbTp06JbYLgoBFixbBysoK2trasLCwQHBwsNKYpk6dis6dO6NTp04YM2YMCgoKxPb4+HjI5XLs3bsXDg4OkEql8PT0xNWrV1Ual0KhwKBBg6Cnpwe5XI6hQ4fi8uXLSmN+1ty5c+Hu7i4+d3d3R1BQEIKCgmBgYABjY2OEhoZCEASxz9O5M2nSJOjp6aFr16747rvvlOKWlpbC29sbUqkU+vr68PX1xfXr18X2RYsWoV+/fli3bh26d+8OHR0dBAQE4NChQ4iJiYFEIoFEIlH590lERERERO1PqxXdMTExWLJkCbp164arV68iKyur1n5RUVHo27cvsrOzERoaitjYWKSkpGDz5s3Iy8tDYmKiWFw/jREXF1dvzGft2rULPj4+8PLyQnZ2NtLS0jBo0CCx/dGjRwgPD8fp06exbds2lJSUICAgQGwPDQ3FhQsXsHv3buTm5mL16tUwNjYWz/Xw8IBMJkN6ejoyMjLEArWqqkql65SWloa8vDzs378fO3fuVCnmnTt34O/vj8OHD+Po0aOws7ODl5cX7ty5AwDYsmULvv32W/zwww8oKCjAtm3b0KdPH/E1AwICcOLECaSkpCAzMxOCIMDLywuPHj0S+9y7dw9RUVFYv349fvvtN5SWlmL+/PkvHc/jx48xfvx4uLm54cyZM8jMzERgYCAkEolK1+OphIQEdOjQAcePH0dMTAyWL1+OdevWKfX55ptvxLnzj3/8A3PmzMH+/fsBADU1NfD29satW7dw6NAh7N+/H5cuXcLEiROVYhQWFmLLli34z3/+g5ycHMTExMDV1RXTp0/H1atXcfXqVVhaWjYodyIiIiIiakeEVvTtt98K1tbW4nM3Nzdhzpw54nNra2th/PjxSufMnj1bGDFihFBTU1NrTADC1q1bVc7B1dVV8PPzU7l/VlaWAEC4c+eOIAiCMG7cOOGjjz6qte/69esFe3t7pVwfPnwo6OrqCnv37n3pa/n7+wumpqbCw4cPmxSzurpakMlkwo4dOwRBEITo6GihZ8+eQlVV1Qt98/PzBQBCRkaGeOzmzZuCrq6usHnzZkEQBCEuLk4AIBQWFop9vvvuO8HU1PSlYyorKxMACAqFos4xe3t7Kx2bM2eO4ObmJj53c3MTHBwclK7BggULBAcHB/G5tbW14OnpqRRn4sSJwpgxYwRBEIR9+/YJmpqaQmlpqdh+/vx5AYBw/PhxQRAEISwsTOjYsaNw48YNpTjPz9O6PHjwQKioqBAfV65cEQAIFRUVLz2XiIiIiIjatoqKCpXe37f5rwxzdnZWeh4QEICcnBzY29sjODgY+/bta1L8nJwcjBw5ss72kydPYty4cbCysoJMJoObmxuAJ1uTAWDmzJlISkpCv3798MUXX+DIkSPiuadPn0ZhYSFkMhmkUimkUikMDQ3x4MEDFBUVqZRfnz59lD5HrErM69evY/r06bCzs4OBgQH09fVRWVkp5vzBBx/g/v37sLW1xfTp07F161Y8fvwYAJCbm4sOHTpg8ODB4msaGRnB3t4eubm54rFOnTrhjTfeEJ+bm5srbbuvi6GhIQICAuDh4YFx48YhJiZG5W3pz3rrrbeUVsddXV1RUFCA6upqpWPPcnV1FceQm5sLS0tLpVXqXr16QS6XK43T2toaJiYmDc4PACIiImBgYCA+uCJORERERNT+tPmiW09PT+n5gAEDUFxcjPDwcNy/fx++vr54//33Gx2/vrul3717Fx4eHtDX10diYiKysrKwdetWABC3co8ZMwaXL1/Gp59+ij/++AMjR44Ut1lXVlZi4MCByMnJUXrk5+dj8uTJKuX3/PhVienv7y9uhT5y5AhycnJgZGQk5mxpaYm8vDx8//330NXVxSeffILhw4crbR9/mY4dOyo9l0gkSp+prk9cXBwyMzMxZMgQbNq0CT179sTRo0cBABoaGi/EaUheze35698QISEhqKioEB9XrlxpxsyIiIiIiOhV0OaL7tro6+tj4sSJWLt2LTZt2oQtW7bg1q1bAJ4Ug8+udr6Mk5MT0tLSam27ePEiysrKEBkZiWHDhuHNN9+sdTXXxMQE/v7+2LBhA1asWIE1a9YAePIHgoKCAnTp0gU9evRQehgYGDRi5KrFzMjIQHBwMLy8vODo6AhtbW3cvHlTKY6uri7GjRuH2NhYKBQKZGZm4uzZs3BwcMDjx49x7NgxsW9ZWRny8vLQq1evRuVcm/79+yMkJARHjhxB79698csvvwB4ci2fX/nOycl54fxn8wMgfnZdU1NT6djzfRwcHAAADg4OuHLlilIhfOHCBfz5558vHaeWlpZKc0xbWxv6+vpKDyIiIiIial9euaJ7+fLl2LhxIy5evIj8/HwkJyfDzMwMcrkcwJO7VqelpeHatWsoLy9/abywsDBs3LgRYWFhyM3NxdmzZ7F06VIAgJWVFbS0tLBy5UpcunQJKSkpCA8PVzp/4cKF2L59OwoLC3H+/Hns3LlTLOz8/PxgbGwMb29vpKeno7i4GAqFAsHBwfj9998bNX5VYtrZ2WH9+vXIzc3FsWPH4Ofnp7SiHx8fjx9//BHnzp3DpUuXsGHDBujq6sLa2hp2dnbw9vbG9OnTcfjwYZw+fRp/+9vf0LVrV3h7ezcq52cVFxcjJCQEmZmZuHz5Mvbt24eCggLxmo0YMQInTpzAzz//jIKCAoSFheHcuXMvxCktLcVnn32GvLw8bNy4EStXrsScOXOU+mRkZGDZsmXIz8/Hd999h+TkZLHPqFGj0KdPH/j5+eHUqVM4fvw4pk6dCjc3txc+0vA8GxsbHDt2DCUlJbh58yZqamqafF2IiIiIiOj19MoV3TKZDMuWLYOzszNcXFxQUlKC1NRUaGg8GUp0dDT2798PS0tL9O/f/6Xx3N3dkZycjJSUFPTr1w8jRozA8ePHATxZdY2Pj0dycjJ69eqFyMhIREVFKZ2vpaWFkJAQODk5Yfjw4dDU1ERSUhKAJ597/u2332BlZYX33nsPDg4OmDZtGh48eNDoVU9VYv74448oLy/HgAEDMGXKFAQHB6NLly5iDLlcjrVr12Lo0KFwcnLCgQMHsGPHDhgZGQF4sv174MCBGDt2LFxdXSEIAlJTU1/YUt7Y/C9evIgJEyagZ8+eCAwMxKxZszBjxgwAgIeHB0JDQ/HFF1/AxcUFd+7cwdSpU1+IM3XqVNy/fx+DBg3CrFmzMGfOHAQGBir1mTdvHk6cOIH+/fvjyy+/xPLly+Hh4QHgyXb47du3o3Pnzhg+fDhGjRoFW1tbbNq06aVjmD9/PjQ1NdGrVy+YmJiIn5UnIiIiIiJ6nkRQ9YO4RG2Eu7s7+vXrhxUrVtTZx8bGBnPnzlX63vfWdvv2bRgYGKCiooJbzYmIiIiIXnGqvr9/5Va6iYiIiIiIiF4Vr33R7ejoKH611vOPxMTEVs2trrykUinS09NbNbemeF3HRURERERE1FCv/fbyy5cv1/mVU6amppDJZC2c0f+vsLCwzrauXbvW+3VmbdnrOq6m4vZyIiIiIqLXh6rv7zu0YE6twtraurVTqFOPHj1aOwW1eF3HRURERERE1FCv/fZyIiIiIiIiotbCopuIiIiIiIhITVh0ExEREREREakJi24iIiIiIiIiNWHRTURERERERKQmLLqJiIiIiIiI1IRFNxEREREREZGasOgmIiIiIiIiUhMW3URERERERERqwqKbiIiIiIiISE06tHYCRO1NWfpmVOl1au006DVh7D65tVMgIiIionpwpZuIiIiIiIhITVh0ExEREREREakJi24iIiIiIiIiNWHRTURERERERKQmLLqJiIiIiIiI1IRFNxEREREREZGasOgmIiIiIiIiUpM2W3QLgoDAwEAYGhpCIpFALpdj7ty5rZ3WK0MikWDbtm2tnYZKAgICMH78+NZOo14lJSWQSCTIyckBACgUCkgkEvz555+tmhcREREREbVtHVo7gbrs2bMH8fHxUCgUsLW1hYaGBnR1dZsUUyKRYOvWrW2+wKO2x9LSElevXoWxsXFrp0JERERERK+QNlt0FxUVwdzcHEOGDFGpf1VVFbS0tNScFbVXmpqaMDMza+00iIiIiIjoFdMmt5cHBARg9uzZKC0thUQigY2NDdzd3ZW2l9vY2CA8PBxTp06Fvr4+AgMDUVVVhaCgIJibm0NHRwfW1taIiIgQ+wOAj4+PGFMVO3bsgIuLC3R0dGBsbAwfHx+xbf369XB2doZMJoOZmRkmT56MGzduiO3l5eXw8/ODiYkJdHV1YWdnh7i4OLH9ypUr8PX1hVwuh6GhIby9vVFSUqLydfrpp5/g6OgIbW1tmJubIygoSKn95s2b8PHxQadOnWBnZ4eUlBSxrbq6GtOmTUP37t2hq6sLe3t7xMTEKJ3/dNt3VFQUzM3NYWRkhFmzZuHRo0diHxsbG3z99df4+OOPIZPJYGVlhTVr1ijFaeo4n1VTU4OIiAgx7759++LXX38V259u+967dy/69+8PXV1djBgxAjdu3MDu3bvh4OAAfX19TJ48Gffu3RPP27NnD95++23I5XIYGRlh7NixKCoqEtuf315ORERERESkijZZdMfExGDJkiXo1q0brl69iqysrFr7RUVFoW/fvsjOzkZoaChiY2ORkpKCzZs3Iy8vD4mJiWJx/TRGXFxcvTGftWvXLvj4+MDLywvZ2dlIS0vDoEGDxPZHjx4hPDwcp0+fxrZt21BSUoKAgACxPTQ0FBcuXMDu3buRm5uL1atXi9uTHz16BA8PD8hkMqSnpyMjIwNSqRSenp6oqqp6aW6rV6/GrFmzEBgYiLNnzyIlJQU9evRQ6rN48WL4+vrizJkz8PLygp+fH27dugXgSfHarVs3JCcn48KFC1i4cCH++c9/YvPmzUoxDh48iKKiIhw8eBAJCQmIj49HfHy8Up/o6Gg4OzsjOzsbn3zyCWbOnIm8vLxmGefzIiIi8PPPP+Pf//43zp8/j08//RR/+9vfcOjQIaV+ixYtwqpVq3DkyBGx6F+xYgV++eUX7Nq1C/v27cPKlSvF/nfv3sVnn32GEydOIC0tDRoaGvDx8UFNTU2Dc3zq4cOHuH37ttKDiIiIiIjalza5vdzAwAAymeylW3pHjBiBefPmic9LS0thZ2eHt99+GxKJBNbW1mKbiYkJAEAul6u8Tfirr77Chx9+iMWLF4vH+vbtK/788ccfiz/b2toiNjYWLi4uqKyshFQqRWlpKfr37w9nZ2cAUFpd37RpE2pqarBu3TpIJBIAT/4gIJfLoVAo8O6779ab25dffol58+Zhzpw54jEXFxelPgEBAZg0aRIA4Ouvv0ZsbCyOHz8OT09PdOzYUWlc3bt3R2ZmJjZv3gxfX1/xeOfOnbFq1SpoamrizTffxF/+8hekpaVh+vTpYh8vLy988sknAIAFCxbg22+/xcGDB2Fvb9/kcT7r4cOH+Prrr3HgwAG4uroCeHLdDx8+jB9++AFubm5K12fo0KEAgGnTpiEkJARFRUWwtbUFALz//vs4ePAgFixYAACYMGGC0mv99NNPMDExwYULF9C7d2+Vc3xWRESE0jUmIiIiIqL2p02udKvqaTH7VEBAAHJycmBvb4/g4GDs27evSfFzcnIwcuTIOttPnjyJcePGwcrKCjKZTCz6SktLAQAzZ85EUlIS+vXrhy+++AJHjhwRzz19+jQKCwshk8kglUohlUphaGiIBw8eKG1rrs2NGzfwxx9/1JsbADg5OYk/6+npQV9fX2n7+3fffYeBAwfCxMQEUqkUa9asEXN/ytHREZqamuJzc3NzpRjPv45EIoGZmZnYpynjfF5hYSHu3buH0aNHi7GkUil+/vnnF2I9m5OpqSk6deokFtxPjz07joKCAkyaNAm2trbQ19cX/0Dy/PVoiJCQEFRUVIiPK1euNDoWERERERG9mtrkSreq9PT0lJ4PGDAAxcXF2L17Nw4cOABfX1+MGjVK6TO/DVHf3dLv3r0LDw8PeHh4IDExESYmJigtLYWHh4e4bXrMmDG4fPkyUlNTsX//fowcORKzZs1CVFQUKisrMXDgQCQmJr4Q++mqfGPyelbHjh2VnkskEnG7dFJSEubPn4/o6Gi4urpCJpPhm2++wbFjx1SOoUqfpozzeZWVlQCebPvv2rWrUpu2tnadOUkkkpeOY9y4cbC2tsbatWthYWGBmpoa9O7du1Fb4J/N6fm8iIiIiIiofXmli+7a6OvrY+LEiZg4cSLef/99eHp64tatWzA0NETHjh1RXV2tciwnJyekpaXho48+eqHt4sWLKCsrQ2RkJCwtLQEAJ06ceKGfiYkJ/P394e/vj2HDhuHzzz9HVFQUBgwYgE2bNqFLly7Q19dv0BhlMhlsbGyQlpaGd955p0HnPpWRkYEhQ4aI28IBNHjlWRVNGefzevXqBW1tbZSWliptJW+qsrIy5OXlYe3atRg2bBgA4PDhw80Wn4iIiIiI2q9Xenv585YvX46NGzfi4sWLyM/PR3JyMszMzCCXywFALFSvXbuG8vLyl8YLCwvDxo0bERYWhtzcXJw9exZLly4FAFhZWUFLSwsrV67EpUuXkJKSgvDwcKXzFy5ciO3bt6OwsBDnz5/Hzp074eDgAADw8/ODsbExvL29kZ6ejuLiYigUCgQHB+P3339/aW6LFi1CdHQ0YmNjUVBQgFOnTindGOxl7OzscOLECezduxf5+fkIDQ1V6eZyDdXUcT5LJpNh/vz5+PTTT5GQkICioiJx3AkJCY3OsXPnzjAyMsKaNWtQWFiI//73v/jss88aHY+IiIiIiOip16rolslkWLZsGZydneHi4oKSkhKkpqZCQ+PJMKOjo7F//35YWlqif//+L43n7u6O5ORkpKSkoF+/fhgxYgSOHz8O4MkKdnx8PJKTk9GrVy9ERkYiKipK6XwtLS2EhITAyckJw4cPh6amJpKSkgAAnTp1wm+//QYrKyu89957cHBwwLRp0/DgwQOVVoT9/f2xYsUKfP/993B0dMTYsWNRUFCg8rWaMWMG3nvvPUycOBGDBw9GWVmZ0qp3c2nqOJ8XHh6O0NBQREREwMHBAZ6enti1axe6d+/e6Bw1NDSQlJSEkydPonfv3vj000/xzTffNDoeERERERHRUxJBEITWToKoPbh9+zYMDAxwaedayPQ6tXY69Jowdp/c2ikQERERtUtP399XVFTUu6D4Wq10ExEREREREbUl7brodnR0VPrqqWcftd1tuyXVlZdUKkV6enqr5qYupaWl9Y67KV/fRURERERE1Bpeu7uXN0RqaioePXpUa5upqWkLZ6MsJyenzrbnvy7rdWFhYVHvuC0sLFouGSIiIiIiombQrotua2vr1k6hTj169GjtFFpchw4d2uW4iYiIiIjo9dWut5cTERERERERqROLbiIiIiIiIiI1YdFNREREREREpCbt+jPdRK3BaJhvvd/jR0RERERErw+udBMRERERERGpCYtuIiIiIiIiIjVh0U1ERERERESkJiy6iYiIiIiIiNSERTcRERERERGRmvDu5UQtrCIvE4JUr7XTIFILA4e3WzsFIiIiojaFK91EREREREREasKim4iIiIiIiEhNWHQTERERERERqQmLbiIiIiIiIiI1YdFNREREREREpCYsuomIiIiIiIjUhEU3ERERERERkZqw6CYiIiIiIiJSkzZRdAuCgMDAQBgaGkIikUAul2Pu3LmtndYrQyKRYNu2ba2dhkoCAgIwfvz4ZotnY2ODFStWNFs8IiIiIiKi5tShtRMAgD179iA+Ph4KhQK2trbQ0NCArq5uk2JKJBJs3bq1WQs8IiIiIiIiooZoE0V3UVERzM3NMWTIEJX6V1VVQUtLS81ZERERERERETVNq28vDwgIwOzZs1FaWgqJRAIbGxu4u7srbS+3sbFBeHg4pk6dCn19fQQGBqKqqgpBQUEwNzeHjo4OrK2tERERIfYHAB8fHzGmKnbs2AEXFxfo6OjA2NgYPj4+Ytv69evh7OwMmUwGMzMzTJ48GTdu3BDby8vL4efnBxMTE+jq6sLOzg5xcXFi+5UrV+Dr6wu5XA5DQ0N4e3ujpKRE5ev0008/wdHREdra2jA3N0dQUJBS+82bN+Hj44NOnTrBzs4OKSkpYlt1dTWmTZuG7t27Q1dXF/b29oiJiVE6/+m276ioKJibm8PIyAizZs3Co0ePxD42Njb4+uuv8fHHH0Mmk8HKygpr1qxRitPUcT7L3d0dQUFBCAoKgoGBAYyNjREaGgpBEJT63bt3r96czp49ixEjRkBXVxdGRkYIDAxEZWVlg8b+8OFDzJ8/H127doWenh4GDx4MhULRqHEREREREVH70epFd0xMDJYsWYJu3brh6tWryMrKqrVfVFQU+vbti+zsbISGhiI2NhYpKSnYvHkz8vLykJiYKBbXT2PExcXVG/NZu3btgo+PD7y8vJCdnY20tDQMGjRIbH/06BHCw8Nx+vRpbNu2DSUlJQgICBDbQ0NDceHCBezevRu5ublYvXo1jI2NxXM9PDwgk8mQnp6OjIwMSKVSeHp6oqqq6qW5rV69GrNmzUJgYCDOnj2LlJQU9OjRQ6nP4sWL4evrizNnzsDLywt+fn64desWAKCmpgbdunVDcnIyLly4gIULF+Kf//wnNm/erBTj4MGDKCoqwsGDB5GQkID4+HjEx8cr9YmOjoazszOys7PxySefYObMmcjLy2uWcdYmISEBHTp0wPHjxxETE4Ply5dj3bp1Kud09+5deHh4oHPnzsjKykJycjIOHDjwwh8tXjb2oKAgZGZmIikpCWfOnMEHH3wAT09PFBQU1Jn7w4cPcfv2baUHERERERG1LxLh+WXDVrBixQqsWLFCXBF1d3dHv379xBtk2djYoH///ti6dat4TnBwMM6fP48DBw5AIpG8ELOhn+keMmQIbG1tsWHDBpX6nzhxAi4uLrhz5w6kUin++te/wtjYGD/99NMLfTds2IAvv/wSubm5Yq5VVVWQy+XYtm0b3n333Xpfq2vXrvjoo4/w5Zdf1toukUjwr3/9C+Hh4QCeFJpSqRS7d++Gp6dnrecEBQXh2rVr+PXXXwE8We1VKBQoKiqCpqYmAMDX1xcaGhpISkoC8OT3MGzYMKxfvx7AkxvgmZmZYfHixfi///s/lcYZEBCAP//8U6Ubv7m7u+PGjRs4f/68GO8f//gHUlJScOHCBZVyWrt2LRYsWIArV65AT08PAJCamopx48bhjz/+gKmp6UvHXlpaCltbW5SWlsLCwkLMb9SoURg0aBC+/vrrWvNftGgRFi9e/MLx0uN7oC/Ve+n4iV5FBg5vt3YKRERERC3i9u3bMDAwQEVFBfT19evs1+or3apydnZWeh4QEICcnBzY29sjODgY+/bta1L8nJwcjBw5ss72kydPYty4cbCysoJMJoObmxsAoLS0FAAwc+ZMJCUloV+/fvjiiy9w5MgR8dzTp0+jsLAQMpkMUqkUUqkUhoaGePDgAYqKiurN68aNG/jjjz/qzQ0AnJycxJ/19PSgr6+vtP39u+++w8CBA2FiYgKpVIo1a9aIuT/l6OgoFp0AYG5urhTj+deRSCQwMzMT+zRlnHV56623lP6o4urqioKCAlRXV6uUU25uLvr27SsW3AAwdOhQ1NTUiKvhLxv72bNnUV1djZ49e4rjkkqlOHToUL3jCgkJQUVFhfi4cuVKo64BERERERG9utrEjdRU8WzRBAADBgxAcXExdu/ejQMHDsDX1xejRo0SV24bqr67pT/douzh4YHExESYmJigtLQUHh4e4rbpMWPG4PLly0hNTcX+/fsxcuRIzJo1C1FRUaisrMTAgQORmJj4QmwTE5NG5/Wsjh07Kj2XSCSoqakBACQlJWH+/PmIjo6Gq6srZDIZvvnmGxw7dkzlGKr0aco4m0KVvJsSo7KyEpqamjh58qRSYQ4AUqm0zpja2trQ1tZuUB5ERERERPR6eWWK7tro6+tj4sSJmDhxIt5//314enri1q1bMDQ0RMeOHZVWQ1/GyckJaWlp+Oijj15ou3jxIsrKyhAZGQlLS0sAT7aXP8/ExAT+/v7w9/fHsGHD8PnnnyMqKgoDBgzApk2b0KVLl3q3HdRGJpPBxsYGaWlpeOeddxp07lMZGRkYMmQIPvnkE/FYY1ee69OUcdbl+T8MHD16FHZ2di8Uv3VxcHBAfHw87t69K/7hJiMjAxoaGrC3t1cpRv/+/VFdXY0bN25g2LBhDRsAERERERG1a6/M9vLnLV++HBs3bsTFixeRn5+P5ORkmJmZQS6XA4BYqF67dg3l5eUvjRcWFoaNGzciLCwMubm5OHv2LJYuXQoAsLKygpaWFlauXIlLly4hJSVF/Pz0UwsXLsT27dtRWFiI8+fPY+fOnXBwcAAA+Pn5wdjYGN7e3khPT0dxcTEUCgWCg4Px+++/vzS3RYsWITo6GrGxsSgoKMCpU6ewcuVKla+VnZ0dTpw4gb179yI/Px+hoaEq3VyuoZo6ztqUlpbis88+Q15eHjZu3IiVK1dizpw5DcpJR0cH/v7+OHfuHA4ePIjZs2djypQpMDU1VSlGz5494efnh6lTp+I///kPiouLcfz4cURERGDXrl2NGhcREREREbUPr2zRLZPJsGzZMjg7O8PFxQUlJSVITU2FhsaTIUVHR2P//v2wtLRE//79XxrP3d0dycnJSElJQb9+/TBixAgcP34cwJMV7Pj4eCQnJ6NXr16IjIxEVFSU0vlaWloICQmBk5MThg8fDk1NTfEGZJ06dcJvv/0GKysrvPfee3BwcMC0adPw4MEDlVaE/f39sWLFCnz//fdwdHTE2LFj671r9vNmzJiB9957DxMnTsTgwYNRVlamtOrdXJo6ztpMnToV9+/fx6BBgzBr1izMmTMHgYGBDcpp7969uHXrFlxcXPD+++9j5MiRWLVqVYPyiIuLw9SpUzFv3jzY29tj/PjxyMrKgpWVVUOHRERERERE7UibuHs5UW2ev4v9q+7p3Q1593J6nfHu5URERNRevHZ3LyciIiIiIiJ61bSbotvR0VHp656efdR2t+2WVFdeUqkU6enprZqbupSWltY77ue/zoyIiIiIiOhV9ErfvbwhUlNT8ejRo1rbVL2hlrrk5OTU2da1a9eWS6QFWVhY1DtuCwsLKBSKFsuHiIiIiIhIHdpN0W1tbd3aKdSpR48erZ1Ci+vQoUO7HDcREREREbUv7WZ7OREREREREVFLY9FNREREREREpCbtZns5UVthYO/a6O8tJyIiIiKiVwtXuomIiIiIiIjUhEU3ERERERERkZpwezlRCxEEAQBw+/btVs6EiIiIiIia6un7+qfv8+vCopuohZSVlQEALC0tWzkTIiIiIiJqLnfu3IGBgUGd7Sy6iVqIoaEhAKC0tLTe/ympfbl9+zYsLS1x5coV3mCPRJwXVBvOC6oN5wXVhvOiZQiCgDt37sDCwqLefiy6iVqIhsaTWygYGBjwHz96gb6+PucFvYDzgmrDeUG14byg2nBeqJ8qi2m8kRoRERERERGRmrDoJiIiIiIiIlITFt1ELURbWxthYWHQ1tZu7VSoDeG8oNpwXlBtOC+oNpwXVBvOi7ZFIrzs/uZERERERERE1Chc6SYiIiIiIiJSExbdRERERERERGrCopuIiIiIiIhITVh0EzXSd999BxsbG+jo6GDw4ME4fvx4vf2Tk5Px5ptvQkdHB3369EFqaqpSuyAIWLhwIczNzaGrq4tRo0ahoKBAnUMgNWjueREQEACJRKL08PT0VOcQSA0aMi/Onz+PCRMmwMbGBhKJBCtWrGhyTGqbmnteLFq06IV/L9588001joDUoSHzYu3atRg2bBg6d+6Mzp07Y9SoUS/05/uL10Nzzwu+v2hZLLqJGmHTpk347LPPEBYWhlOnTqFv377w8PDAjRs3au1/5MgRTJo0CdOmTUN2djbGjx+P8ePH49y5c2KfZcuWITY2Fv/+979x7Ngx6OnpwcPDAw8ePGipYVETqWNeAICnpyeuXr0qPjZu3NgSw6Fm0tB5ce/ePdja2iIyMhJmZmbNEpPaHnXMCwBwdHRU+vfi8OHD6hoCqUFD54VCocCkSZNw8OBBZGZmwtLSEu+++y7+97//iX34/uLVp455AfD9RYsSiKjBBg0aJMyaNUt8Xl1dLVhYWAgRERG19vf19RX+8pe/KB0bPHiwMGPGDEEQBKGmpkYwMzMTvvnmG7H9zz//FLS1tYWNGzeqYQSkDs09LwRBEPz9/QVvb2+15Esto6Hz4lnW1tbCt99+26wxqW1Qx7wICwsT+vbt24xZUktr6v/bjx8/FmQymZCQkCAIAt9fvC6ae14IAt9ftDSudBM1UFVVFU6ePIlRo0aJxzQ0NDBq1ChkZmbWek5mZqZSfwDw8PAQ+xcXF+PatWtKfQwMDDB48OA6Y1Lboo558ZRCoUCXLl1gb2+PmTNnoqysrPkHQGrRmHnRGjGpZanzd1hQUAALCwvY2trCz88PpaWlTU2XWkhzzIt79+7h0aNHMDQ0BMD3F68DdcyLp/j+ouWw6CZqoJs3b6K6uhqmpqZKx01NTXHt2rVaz7l27Vq9/Z/+tyExqW1Rx7wAnmz9+vnnn5GWloalS5fi0KFDGDNmDKqrq5t/ENTsGjMvWiMmtSx1/Q4HDx6M+Ph47NmzB6tXr0ZxcTGGDRuGO3fuNDVlagHNMS8WLFgACwsLsUDj+4tXnzrmBcD3Fy2tQ2snQEREdfvwww/Fn/v06QMnJye88cYbUCgUGDlyZCtmRkRtzZgxY8SfnZycMHjwYFhbW2Pz5s2YNm1aK2ZGLSEyMhJJSUlQKBTQ0dFp7XSojahrXvD9RcviSjdRAxkbG0NTUxPXr19XOn79+vU6b25jZmZWb/+n/21ITGpb1DEvamNrawtjY2MUFhY2PWlSu8bMi9aISS2rpX6HcrkcPXv25L8Xr4imzIuoqChERkZi3759cHJyEo/z/cWrTx3zojZ8f6FeLLqJGkhLSwsDBw5EWlqaeKympgZpaWlwdXWt9RxXV1el/gCwf/9+sX/37t1hZmam1Of27ds4duxYnTGpbVHHvKjN77//jrKyMpibmzdP4qRWjZkXrRGTWlZL/Q4rKytRVFTEfy9eEY2dF8uWLUN4eDj27NkDZ2dnpTa+v3j1qWNe1IbvL9Sste/kRvQqSkpKErS1tYX4+HjhwoULQmBgoCCXy4Vr164JgiAIU6ZMEf7xj3+I/TMyMoQOHToIUVFRQm5urhAWFiZ07NhROHv2rNgnMjJSkMvlwvbt24UzZ84I3t7eQvfu3YX79++3+PiocZp7Xty5c0eYP3++kJmZKRQXFwsHDhwQBgwYINjZ2QkPHjxolTFSwzV0Xjx8+FDIzs4WsrOzBXNzc2H+/PlCdna2UFBQoHJMavvUMS/mzZsnKBQKobi4WMjIyBBGjRolGBsbCzdu3Gjx8VHjNHReREZGClpaWsKvv/4qXL16VXzcuXNHqQ/fX7zamnte8P1Fy2PRTdRIK1euFKysrAQtLS1h0KBBwtGjR8U2Nzc3wd/fX6n/5s2bhZ49ewpaWlqCo6OjsGvXLqX2mpoaITQ0VDA1NRW0tbWFkSNHCnl5eS0xFGpGzTkv7t27J7z77ruCiYmJ0LFjR8Ha2lqYPn06C6tXUEPmRXFxsQDghYebm5vKMenV0NzzYuLEiYK5ubmgpaUldO3aVZg4caJQWFjYgiOi5tCQeWFtbV3rvAgLCxP78P3F66E55wXfX7Q8iSAIQsuurRMRERERERG1D/xMNxEREREREZGasOgmIiIiIiIiUhMW3URERERERERqwqKbiIiIiIiISE1YdBMRERERERGpCYtuIiIiIiIiIjVh0U1ERERERESkJiy6iYiIiIiIiNSERTcRERERERGRmrDoJiIiIrUKCAjA+PHjWzuNOpWUlEAikSAnJ6e1U1HJ//t//w8zZ86ElZUVtLW1YWZmBg8PD2RkZLR2akREVIsOrZ0AERERUWupqqpq7RQabMKECaiqqkJCQgJsbW1x/fp1pKWloaysTG2vWVVVBS0tLbXFJyJ6nXGlm4iIiFqUu7s7Zs+ejblz56Jz584wNTXF2rVrcffuXXz00UeQyWTo0aMHdu/eLZ6jUCggkUiwa9cuODk5QUdHB2+99RbOnTunFHvLli1wdHSEtrY2bGxsEB0drdRuY2OD8PBwTJ06Ffr6+ggMDET37t0BAP3794dEIoG7uzsAICsrC6NHj4axsTEMDAzg5uaGU6dOKcWTSCRYt24dfHx80KlTJ9jZ2SElJUWpz/nz5zF27Fjo6+tDJpNh2LBhKCoqEtvXrVsHBwcH6Ojo4M0338T3339f57X7888/kZ6ejqVLl+Kdd96BtbU1Bg0ahJCQEPz1r39V6jdjxgyYmppCR0cHvXv3xs6dO5t0nQDg8OHDGDZsGHR1dWFpaYng4GDcvXu3znyJiIhFNxEREbWChIQEGBsb4/jx45g9ezZmzpyJDz74AEOGDMGpU6fw7rvvYsqUKbh3757SeZ9//jmio6ORlZUFExMTjBs3Do8ePQIAnDx5Er6+vvjwww9x9uxZLFq0CKGhoYiPj1eKERUVhb59+yI7OxuhoaE4fvw4AODAgQO4evUq/vOf/wAA7ty5A39/fxw+fBhHjx6FnZ0dvLy8cOfOHaV4ixcvhq+vL86cOQMvLy/4+fnh1q1bAID//e9/GD58OLS1tfHf//4XJ0+exMcff4zHjx8DABITE7Fw4UJ89dVXyM3Nxddff43Q0FAkJCTUet2kUimkUim2bduGhw8f1tqnpqYGY8aMQUZGBjZs2IALFy4gMjISmpqaTbpORUVF8PT0xIQJE3DmzBls2rQJhw8fRlBQUH2/aiIiEoiIiIjUyN/fX/D29hafu7m5CW+//bb4/PHjx4Kenp4wZcoU8djVq1cFAEJmZqYgCIJw8OBBAYCQlJQk9ikrKxN0dXWFTZs2CYIgCJMnTxZGjx6t9Nqff/650KtXL/G5tbW1MH78eKU+xcXFAgAhOzu73nFUV1cLMplM2LFjh3gMgPCvf/1LfF5ZWSkAEHbv3i0IgiCEhIQI3bt3F6qqqmqN+cYbbwi//PKL0rHw8HDB1dW1zjx+/fVXoXPnzoKOjo4wZMgQISQkRDh9+rTYvnfvXkFDQ0PIy8ur9fzGXqdp06YJgYGBSsfS09MFDQ0N4f79+3XmS0TU3nGlm4iIiFqck5OT+LOmpiaMjIzQp08f8ZipqSkA4MaNG0rnubq6ij8bGhrC3t4eubm5AIDc3FwMHTpUqf/QoUNRUFCA6upq8Zizs7NKOV6/fh3Tp0+HnZ0dDAwMoK+vj8rKSpSWltY5Fj09Pejr64t55+TkYNiwYejYseML8e/evYuioiJMmzZNXMGWSqX48ssvlbafP2/ChAn4448/kJKSAk9PTygUCgwYMEBcqc7JyUG3bt3Qs2fPWs9v7HU6ffo04uPjlXL18PBATU0NiouL68yXiKi9443UiIiIqMU9X4RKJBKlYxKJBMCTrdLNTU9PT6V+/v7+KCsrQ0xMDKytraGtrQ1XV9cXbr5W21ie5q2rq1tn/MrKSgDA2rVrMXjwYKW2p1vB66Kjo4PRo0dj9OjRCA0Nxd///neEhYUhICCg3tdsiOevU2VlJWbMmIHg4OAX+lpZWTXLaxIRvY5YdBMREdEr4+jRo2KBV15ejvz8fDg4OAAAHBwcXvjarIyMDPTs2bPeIvbpXbmfXeV9eu73338PLy8vAMCVK1dw8+bNBuXr5OSEhIQEPHr06IXi3NTUFBYWFrh06RL8/PwaFPd5vXr1wrZt28TX/P3335Gfn1/randjr9OAAQNw4cIF9OjRo0m5EhG1N9xeTkRERK+MJUuWIC0tDefOnUNAQACMjY3F7wCfN28e0tLSEB4ejvz8fCQkJGDVqlWYP39+vTG7dOkCXV1d7NmzB9evX0dFRQUAwM7ODuvXr0dubi6OHTsGPz+/Bq8iBwUF4fbt2/jwww9x4sQJFBQUYP369cjLywPw5CZsERERiI2NRX5+Ps6ePYu4uDgsX7681nhlZWUYMWIENmzYgDNnzqC4uBjJyclYtmwZvL29AQBubm4YPnw4JkyYgP3796O4uBi7d+/Gnj17mnSdFixYgCNHjiAoKAg5OTkoKCjA9u3beSM1IqKXYNFNREREr4zIyEjMmTMHAwcOxLVr17Bjxw5xpXrAgAHYvHkzkpKS0Lt3byxcuBBLlixBQEBAvTE7dOiA2NhY/PDDD7CwsBCL1x9//BHl5eUYMGAApkyZguDgYHTp0qVB+RoZGeG///0vKisr4ebmhoEDB2Lt2rXiqvff//53rFu3DnFxcejTpw/c3NwQHx8vfo3Z86RSKQYPHoxvv/0Ww4cPR+/evREaGorp06dj1apVYr8tW7bAxcUFkyZNQq9evfDFF1+IK/mNvU5OTk44dOgQ8vPzMWzYMPTv3x8LFy6EhYVFg64JEVF7IxEEQWjtJIiIiIjqo1Ao8M4776C8vBxyuby10yEiIlIZV7qJiIiIiIiI1IRFNxEREREREZGacHs5ERERERERkZpwpZuIiIiIiIhITVh0ExEREREREakJi24iIiIiIiIiNWHRTURERERERKQmLLqJiIiIiIiI1IRFNxEREREREZGasOgmIiIiIiIiUhMW3URERERERERqwqKbiIiIiIiISE3+P+ZhyNn60CuVAAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "new_xgb_metrics = evaluate_model(xgb_model_new, X_test_new, y_test_new, 'new Churn XGB Baseline')\n", "\n", "try:\n", " new_importance_scores = xgb_model_new.feature_importances_\n", " new_feature_importance_df = pd.DataFrame({\n", " 'Feature': final_new_feature_names,\n", " 'Importance': new_importance_scores\n", " })\n", "\n", " new_feature_importance_df.sort_values(by='Importance', ascending=False)\n", "\n", " top_n_new = 15\n", "\n", " print(f'\\nTop {top_n_new} Features by Importance')\n", " print(new_feature_importance_df.head(top_n_new))\n", "\n", " plt.figure(figsize=(10,6))\n", " sns.barplot(x='Importance', y='Feature', data=new_feature_importance_df.head(top_n_new), palette='rocket')\n", " plt.title(f'Top {top_n_new} Feature Importances')\n", " plt.xlabel('Importance Score')\n", " plt.ylabel('Feature')\n", " plt.tight_layout()\n", " plt.show\n", "\n", "except Exception as e:\n", " print(f'Could not generate feature importance plot {e}')" ] }, { "cell_type": "markdown", "id": "b4d3f26e", "metadata": { "papermill": { "duration": 0.047486, "end_time": "2025-04-22T05:39:54.010382", "exception": false, "start_time": "2025-04-22T05:39:53.962896", "status": "completed" }, "tags": [] }, "source": [ "Abysmal performance on the current model. Will try tuning it" ] }, { "cell_type": "code", "execution_count": 66, "id": "e8b71b3f", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:39:54.107188Z", "iopub.status.busy": "2025-04-22T05:39:54.106799Z", "iopub.status.idle": "2025-04-22T05:39:54.113851Z", "shell.execute_reply": "2025-04-22T05:39:54.112681Z" }, "papermill": { "duration": 0.057674, "end_time": "2025-04-22T05:39:54.115680", "exception": false, "start_time": "2025-04-22T05:39:54.058006", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "xgb_base_new = xgb.XGBClassifier(\n", " objective = 'binary:logistic',\n", " eval_metric='logloss',\n", " use_label_encoder = False,\n", " random_state = 0\n", ")\n", "\n", "param_distributions = {\n", " 'n_estimators': [int(x) for x in np.linspace(start = 100, stop=1000, num=10)],\n", " 'max_depth': [3,4,5,6,7,8],\n", " 'learning_rate': [0.01, 0.05, 0.1, 0.2],\n", " 'scale_pos_weight': [5,10,15,20,24],\n", " 'subsample': [0.7,0.8,0.9,1.0],\n", " 'colsample_bytree': [0.7, 0.8, 0.9, 1.0]\n", "}\n", "\n", "n_iterations = 50\n", "\n", "cv_folds = 3\n", "\n", "scoring_metric = 'average_precision'\n", "\n", "random_search_new = RandomizedSearchCV(\n", " estimator = xgb_base_new,\n", " param_distributions = param_distributions,\n", " n_iter = n_iterations,\n", " scoring = scoring_metric,\n", " n_jobs = -1,\n", " cv = cv_folds,\n", " verbose = 1,\n", " random_state = 0\n", ")" ] }, { "cell_type": "code", "execution_count": 67, "id": "a7c51add", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:39:54.214426Z", "iopub.status.busy": "2025-04-22T05:39:54.214039Z", "iopub.status.idle": "2025-04-22T05:57:48.031230Z", "shell.execute_reply": "2025-04-22T05:57:48.029826Z" }, "papermill": { "duration": 1073.918026, "end_time": "2025-04-22T05:57:48.082785", "exception": false, "start_time": "2025-04-22T05:39:54.164759", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fitting 3 folds for each of 50 candidates, totalling 150 fits\n" ] }, { "data": { "text/html": [ "
RandomizedSearchCV(cv=3,\n",
       "                   estimator=XGBClassifier(base_score=None, booster=None,\n",
       "                                           callbacks=None,\n",
       "                                           colsample_bylevel=None,\n",
       "                                           colsample_bynode=None,\n",
       "                                           colsample_bytree=None, device=None,\n",
       "                                           early_stopping_rounds=None,\n",
       "                                           enable_categorical=False,\n",
       "                                           eval_metric='logloss',\n",
       "                                           feature_types=None, gamma=None,\n",
       "                                           grow_policy=None,\n",
       "                                           importance_type=None,\n",
       "                                           interaction_constraints=None,\n",
       "                                           learning...\n",
       "                                           num_parallel_tree=None,\n",
       "                                           random_state=0, ...),\n",
       "                   n_iter=50, n_jobs=-1,\n",
       "                   param_distributions={'colsample_bytree': [0.7, 0.8, 0.9,\n",
       "                                                             1.0],\n",
       "                                        'learning_rate': [0.01, 0.05, 0.1, 0.2],\n",
       "                                        'max_depth': [3, 4, 5, 6, 7, 8],\n",
       "                                        'n_estimators': [100, 200, 300, 400,\n",
       "                                                         500, 600, 700, 800,\n",
       "                                                         900, 1000],\n",
       "                                        'scale_pos_weight': [5, 10, 15, 20, 24],\n",
       "                                        'subsample': [0.7, 0.8, 0.9, 1.0]},\n",
       "                   random_state=0, scoring='average_precision', verbose=1)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" ], "text/plain": [ "RandomizedSearchCV(cv=3,\n", " estimator=XGBClassifier(base_score=None, booster=None,\n", " callbacks=None,\n", " colsample_bylevel=None,\n", " colsample_bynode=None,\n", " colsample_bytree=None, device=None,\n", " early_stopping_rounds=None,\n", " enable_categorical=False,\n", " eval_metric='logloss',\n", " feature_types=None, gamma=None,\n", " grow_policy=None,\n", " importance_type=None,\n", " interaction_constraints=None,\n", " learning...\n", " num_parallel_tree=None,\n", " random_state=0, ...),\n", " n_iter=50, n_jobs=-1,\n", " param_distributions={'colsample_bytree': [0.7, 0.8, 0.9,\n", " 1.0],\n", " 'learning_rate': [0.01, 0.05, 0.1, 0.2],\n", " 'max_depth': [3, 4, 5, 6, 7, 8],\n", " 'n_estimators': [100, 200, 300, 400,\n", " 500, 600, 700, 800,\n", " 900, 1000],\n", " 'scale_pos_weight': [5, 10, 15, 20, 24],\n", " 'subsample': [0.7, 0.8, 0.9, 1.0]},\n", " random_state=0, scoring='average_precision', verbose=1)" ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ "random_search_new.fit(X_train_new, y_train_new)" ] }, { "cell_type": "code", "execution_count": 68, "id": "6deb0fd8", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:57:48.234829Z", "iopub.status.busy": "2025-04-22T05:57:48.234401Z", "iopub.status.idle": "2025-04-22T05:57:48.240640Z", "shell.execute_reply": "2025-04-22T05:57:48.239431Z" }, "papermill": { "duration": 0.110832, "end_time": "2025-04-22T05:57:48.242288", "exception": false, "start_time": "2025-04-22T05:57:48.131456", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Best Score (average_precision) found: 0.0370\n", "{'subsample': 0.7, 'scale_pos_weight': 24, 'n_estimators': 200, 'max_depth': 3, 'learning_rate': 0.05, 'colsample_bytree': 0.8}\n" ] } ], "source": [ "print(f'Best Score ({scoring_metric}) found: {random_search_new.best_score_:.4f}')\n", "print(random_search_new.best_params_)\n", "\n", "best_xgb_model_new = random_search_new.best_estimator_" ] }, { "cell_type": "code", "execution_count": 69, "id": "7fd35c1b", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:57:48.340686Z", "iopub.status.busy": "2025-04-22T05:57:48.340288Z", "iopub.status.idle": "2025-04-22T05:57:49.324978Z", "shell.execute_reply": "2025-04-22T05:57:49.323665Z" }, "papermill": { "duration": 1.036419, "end_time": "2025-04-22T05:57:49.326936", "exception": false, "start_time": "2025-04-22T05:57:48.290517", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Evaluation Report for new Churn Tuned XGB\n", " precision recall f1-score support\n", "\n", "No Churn (0) 0.97 0.76 0.86 98671\n", " Churn (1) 0.04 0.32 0.07 3116\n", "\n", " accuracy 0.75 101787\n", " macro avg 0.51 0.54 0.46 101787\n", "weighted avg 0.94 0.75 0.83 101787\n", "\n", "ROC AUC Score: 0.5609\n", "Precision-Recall Curve AUC (PRC AUC): 0.0373\n", "\n", " Confusion Matrix:\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "tuned_xgb_new_metrics = evaluate_model(\n", " best_xgb_model_new,\n", " X_test_new,\n", " y_test_new,\n", " 'new Churn Tuned XGB'\n", ")" ] }, { "cell_type": "markdown", "id": "ee5492d0", "metadata": { "papermill": { "duration": 0.050026, "end_time": "2025-04-22T05:57:49.427496", "exception": false, "start_time": "2025-04-22T05:57:49.377470", "status": "completed" }, "tags": [] }, "source": [ "The tuning process confirms the findings from the baseline model: The features currently available and engineered for predicting churn within the first 90 days lack sufficient predictive power. Even with optimized hyperparameters, the XGBoost model cannot reliably identify customers who will churn new based only on product info, demographics, signup timing, and basic first contact information." ] }, { "cell_type": "markdown", "id": "26df327c", "metadata": { "papermill": { "duration": 0.049414, "end_time": "2025-04-22T05:57:49.527330", "exception": false, "start_time": "2025-04-22T05:57:49.477916", "status": "completed" }, "tags": [] }, "source": [ "### Individual Prediction Explanation (using SHAP)" ] }, { "cell_type": "code", "execution_count": 70, "id": "d42b9204", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:57:49.628963Z", "iopub.status.busy": "2025-04-22T05:57:49.628587Z", "iopub.status.idle": "2025-04-22T05:57:50.676973Z", "shell.execute_reply": "2025-04-22T05:57:50.675846Z" }, "papermill": { "duration": 1.101372, "end_time": "2025-04-22T05:57:50.678958", "exception": false, "start_time": "2025-04-22T05:57:49.577586", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Actual_Churn Predicted_Probability\n", "106273 1 0.999996\n", "113177 1 0.999993\n", "109789 1 0.999990\n", "439767 1 0.999986\n", "436756 1 0.999986\n", "453122 1 0.999983\n", "441013 1 0.999982\n", "108998 1 0.999982\n", "440203 1 0.999979\n", "446190 1 0.999979" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "Identified 1176 customers above 0.50 probability threshold.\n" ] } ], "source": [ "test_probabilities = best_xgb_model.predict_proba(X_test_est)[:,1]\n", "\n", "results_df = pd.DataFrame({\n", " 'Actual_Churn': y_test_est,\n", " 'Predicted_Probability': test_probabilities\n", "}, index = X_test_est.index)\n", "\n", "results_df_sorted = results_df.sort_values(by='Predicted_Probability', ascending=False)\n", "\n", "display(results_df_sorted.head(10))\n", "\n", "risk_threshold = 0.5\n", "high_risk_list = results_df_sorted[results_df_sorted['Predicted_Probability'] >= risk_threshold]\n", "print(f\"\\nIdentified {len(high_risk_list)} customers above {risk_threshold:.2f} probability threshold.\")" ] }, { "cell_type": "code", "execution_count": 71, "id": "beb5c550", "metadata": { "execution": { "iopub.execute_input": "2025-04-22T05:57:50.782537Z", "iopub.status.busy": "2025-04-22T05:57:50.782153Z", "iopub.status.idle": "2025-04-22T05:57:50.799003Z", "shell.execute_reply": "2025-04-22T05:57:50.797884Z" }, "papermill": { "duration": 0.069469, "end_time": "2025-04-22T05:57:50.800590", "exception": false, "start_time": "2025-04-22T05:57:50.731121", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "idx_high_risk\n" ] }, { "data": { "text/html": [ "\n", "
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\n", " Have you run `initjs()` in this notebook? If this notebook was from another\n", " user you must also trust this notebook (File -> Trust notebook). If you are viewing\n", " this notebook on github the Javascript has been stripped for security. If you are using\n", " JupyterLab this error is because a JupyterLab extension has not yet been written.\n", "
\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "idx_low_risk\n" ] }, { "data": { "text/html": [ "\n", "
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\n", " Visualization omitted, Javascript library not loaded!
\n", " Have you run `initjs()` in this notebook? If this notebook was from another\n", " user you must also trust this notebook (File -> Trust notebook). If you are viewing\n", " this notebook on github the Javascript has been stripped for security. If you are using\n", " JupyterLab this error is because a JupyterLab extension has not yet been written.\n", "
\n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "if 'explainer' in locals() and shap_values is not None:\n", " try:\n", " idx_high_risk = results_df_sorted.index[0]\n", " idx_low_risk = results_df_sorted.index[-1]\n", "\n", " print('idx_high_risk')\n", " display(shap.force_plot(explainer.expected_value,\n", " shap_values[results_df_sorted.index.get_loc(idx_high_risk),:],\n", " X_test_est_df.loc[idx_high_risk,:]))\n", " print('idx_low_risk')\n", " display(shap.force_plot(explainer.expected_value,\n", " shap_values[results_df_sorted.index.get_loc(idx_low_risk),:],\n", " X_test_est_df.loc[idx_low_risk,:]))\n", " except IndexError:\n", " print(\"Could not retrieve example indices. Ensure results_df_sorted is populated.\")\n", " except Exception as e:\n", " print(f\"Could not generate force plots: {e}\")\n", "\n", "else:\n", " print(\"SHAP explainer or values not available for force plots.\")\n", " " ] } ], "metadata": { "kaggle": { "accelerator": "none", "dataSources": [ { "datasetId": 2290183, "sourceId": 3852264, "sourceType": "datasetVersion" } ], "dockerImageVersionId": 30918, "isGpuEnabled": false, "isInternetEnabled": true, "language": "python", "sourceType": "notebook" }, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.12" }, "papermill": { "default_parameters": {}, "duration": 2506.950271, "end_time": "2025-04-22T05:57:53.185800", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2025-04-22T05:16:06.235529", "version": "2.6.0" } }, "nbformat": 4, "nbformat_minor": 5 }